Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/5B405297-DDAB-42B3-9D20-0F4417E84693 | - |
| Αναγνωριστικό | http://ebooks.iospress.nl/publication/44756 | - |
| Αναγνωριστικό | https://doi.org/10.3233/978-1-61499-672-9-175 | - |
| Γλώσσα | en | - |
| Μέγεθος | 9 pages | en |
| Τίτλος | Decentralized large-scale electricity consumption shifting by prosumer cooperatives | en |
| Δημιουργός | Akasiadis Charilaos | en |
| Δημιουργός | Ακασιαδης Χαριλαος | el |
| Δημιουργός | Chalkiadakis Georgios | en |
| Δημιουργός | Χαλκιαδακης Γεωργιος | el |
| Εκδότης | IOS Press | en |
| Περίληψη | 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 |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2018-10-29 | - |
| Ημερομηνία Δημοσίευσης | 2016 | - |
| Θεματική Κατηγορία | Electricity consumption | en |
| Βιβλιογραφική Αναφορά | 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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