Agent-Based Optimization To Estimate Nash Equilibrium in Power Markets
| gdc.relation.journal | Energy Sources Part B-Economics Planning And Policy | en_US |
| dc.contributor.author | Yücekaya, Ahmet | |
| dc.contributor.author | Valenzuela, Jorge | |
| dc.contributor.other | Industrial Engineering | |
| dc.contributor.other | 05. Faculty of Engineering and Natural Sciences | |
| dc.contributor.other | 01. Kadir Has University | |
| dc.date.accessioned | 2019-06-27T08:03:39Z | |
| dc.date.available | 2019-06-27T08:03:39Z | |
| dc.date.issued | 2013 | |
| dc.description.abstract | In most deregulated power markets firms bid daily into a day-ahead power market. The auction mechanism supply and demand determine the equilibrium at each hour. In this environment firms aim to maximize their revenues by carefully determining their bids. This requires the development of effective computational methods that help them estimate their competitors' behaviors under incomplete information. In this article an agent-based method that uses particle swarm optimization is described to simulate the behavior of market participants. Particle swarm optimization is used in the bidding process and an agent-based model is applied to find a Nash equilibrium. Different stopping conditions are used to determine the equilibrium. Experimental results are presented for two power systems. | en_US] |
| dc.identifier.citationcount | 4 | |
| dc.identifier.doi | 10.1080/15567249.2011.578103 | en_US |
| dc.identifier.issn | 1556-7249 | en_US |
| dc.identifier.issn | 1556-7249 | |
| dc.identifier.issn | 1556-7257 | |
| dc.identifier.scopus | 2-s2.0-84872482549 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12469/821 | |
| dc.identifier.uri | https://doi.org/10.1080/15567249.2011.578103 | |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor & Francis Inc | en_US |
| dc.relation.ispartof | Energy Sources, Part B: Economics, Planning, and Policy | |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Agent-based modeling and simulation | en_US |
| dc.subject | Electricity price | en_US |
| dc.subject | Equilibrium | en_US |
| dc.subject | Particle swarm optimization (PSO) | en_US |
| dc.subject | Power markets | en_US |
| dc.subject | Strategic bidding | en_US |
| dc.title | Agent-Based Optimization To Estimate Nash Equilibrium in Power Markets | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Yücekaya, Ahmet | en_US |
| gdc.author.institutional | Yücekaya, Ahmet Deniz | |
| gdc.bip.impulseclass | C5 | |
| gdc.bip.influenceclass | C5 | |
| gdc.bip.popularityclass | C5 | |
| gdc.coar.access | metadata only access | |
| gdc.coar.type | text::journal::journal article | |
| gdc.description.department | Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümü | en_US |
| gdc.description.endpage | 216 | |
| gdc.description.issue | 2 | |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q1 | |
| gdc.description.startpage | 209 | en_US |
| gdc.description.volume | 8 | en_US |
| gdc.identifier.openalex | W1990024116 | |
| gdc.identifier.wos | WOS:000314637200013 | en_US |
| gdc.oaire.diamondjournal | false | |
| gdc.oaire.impulse | 3.0 | |
| gdc.oaire.influence | 3.0553762E-9 | |
| gdc.oaire.isgreen | false | |
| gdc.oaire.keywords | Equilibrium | |
| gdc.oaire.keywords | Agent-based modeling and simulation | |
| gdc.oaire.keywords | Particle swarm optimization (PSO) | |
| gdc.oaire.keywords | Power markets | |
| gdc.oaire.keywords | Strategic bidding | |
| gdc.oaire.keywords | Electricity price | |
| gdc.oaire.popularity | 1.8015314E-9 | |
| gdc.oaire.publicfunded | false | |
| gdc.oaire.sciencefields | 0211 other engineering and technologies | |
| gdc.oaire.sciencefields | 0202 electrical engineering, electronic engineering, information engineering | |
| gdc.oaire.sciencefields | 02 engineering and technology | |
| gdc.openalex.fwci | 0.551 | |
| gdc.openalex.normalizedpercentile | 0.7 | |
| gdc.opencitations.count | 5 | |
| gdc.plumx.crossrefcites | 5 | |
| gdc.plumx.mendeley | 11 | |
| gdc.plumx.scopuscites | 6 | |
| gdc.scopus.citedcount | 6 | |
| gdc.wos.citedcount | 4 | |
| relation.isAuthorOfPublication | 5eb0a05e-38c7-4571-847a-8c1883879f97 | |
| relation.isAuthorOfPublication.latestForDiscovery | 5eb0a05e-38c7-4571-847a-8c1883879f97 | |
| relation.isOrgUnitOfPublication | 28868d0c-e9a4-4de1-822f-c8df06d2086a | |
| relation.isOrgUnitOfPublication | 2457b9b3-3a3f-4c17-8674-7f874f030d96 | |
| relation.isOrgUnitOfPublication | b20623fc-1264-4244-9847-a4729ca7508c | |
| relation.isOrgUnitOfPublication.latestForDiscovery | 28868d0c-e9a4-4de1-822f-c8df06d2086a |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Agent-based Optimization to Estimate Nash Equilibrium in Power Markets.pdf
- Size:
- 467.38 KB
- Format:
- Adobe Portable Document Format
- Description: