Institutional Repository
Technical University of Crete
Technical University of Crete
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EL
| URI | http://purl.tuc.gr/dl/dias/5B405297-DDAB-42B3-9D20-0F4417E84693 | - |
| Identifier | http://ebooks.iospress.nl/publication/44756 | - |
| Identifier | https://doi.org/10.3233/978-1-61499-672-9-175 | - |
| Language | en | - |
| Extent | 9 pages | en |
| Title | Decentralized large-scale electricity consumption shifting by prosumer cooperatives | en |
| Creator | Akasiadis Charilaos | en |
| Creator | Ακασιαδης Χαριλαος | el |
| Creator | Chalkiadakis Georgios | en |
| Creator | Χαλκιαδακης Γεωργιος | el |
| Publisher | IOS Press | en |
| Content Summary | In this work we address the problem of coordinated consumption shifting for electricity prosumers. We show that individual optimization with respect to electricity prices does not always lead to minimized costs, thus necessitating a cooperative approach. A prosumer cooperative employs an internal cryptocurrency mechanism for coordinating members decisions and distributing the collectively generated profits. The mechanism generates cryptocoins in a distributed fashion, and awards them to participants according to various criteria, such as contribution impact and accuracy between stated and final shifting actions. In particular, when a scoring rulesbased distribution method is employed, participants are incentivized to be accurate. When tested on a large dataset with real-world production and consumption data, our approach is shown to provide incentives for accurate statements and increased economic profits for the cooperative. | en |
| Type of Item | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Full Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2018-10-29 | - |
| Date of Publication | 2016 | - |
| Subject | Electricity consumption | en |
| Bibliographic Citation | C. Akasiadis and G. Chalkiadakis, "Decentralized large-scale electricity consumption shifting by prosumer cooperatives," in 22nd European Conference on Artificial Intelligence, 2016, pp. 175-183. doi: 10.3233/978-1-61499-672-9-175 | en |
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