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A learning approach for strategic consumers in smart electricity markets
dc.creator | Foti M., Vavalis M. | en |
dc.date.accessioned | 2023-01-31T07:38:27Z | |
dc.date.available | 2023-01-31T07:38:27Z | |
dc.date.issued | 2016 | |
dc.identifier | 10.1109/IISA.2015.7388043 | |
dc.identifier.isbn | 9781467393119 | |
dc.identifier.uri | http://hdl.handle.net/11615/71689 | |
dc.description.abstract | In this paper we consider the design and the implementation of a machine learning approach and its integration with a widely used energy simulation platform. We focus on auction based energy markets which require their participants to bid for their energy demands or offers at small time intervals. Our agent based system utilize weather data to teach both consuming devices and renewable energy sources to bid in an effective manner. We simulate realistic case studies of a residential distribution power grid with a total of more than 600 households with varying energy requirements. Photovoltaic panels as well as wind turbines are the regional energy resources. Our experimentation exhibit the effectiveness of the learning procedure both in term of power consumption and cost. © 2015 IEEE. | en |
dc.language.iso | en | en |
dc.source | IISA 2015 - 6th International Conference on Information, Intelligence, Systems and Applications | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963851900&doi=10.1109%2fIISA.2015.7388043&partnerID=40&md5=27fa0464430318660fd044666d5ce1d7 | |
dc.subject | Artificial intelligence | en |
dc.subject | Commerce | en |
dc.subject | Demand side management | en |
dc.subject | Electric power transmission networks | en |
dc.subject | Electric utilities | en |
dc.subject | Energy resources | en |
dc.subject | Learning systems | en |
dc.subject | Photovoltaic cells | en |
dc.subject | Power markets | en |
dc.subject | Renewable energy resources | en |
dc.subject | Wind turbines | en |
dc.subject | Distribution power grids | en |
dc.subject | Energy markets | en |
dc.subject | Energy requirements | en |
dc.subject | Learning procedures | en |
dc.subject | Machine learning approaches | en |
dc.subject | Renewable energy source | en |
dc.subject | Smart grid | en |
dc.subject | Strategic bidding | en |
dc.subject | Smart power grids | en |
dc.subject | Institute of Electrical and Electronics Engineers Inc. | en |
dc.title | A learning approach for strategic consumers in smart electricity markets | en |
dc.type | conferenceItem | en |
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