Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI: | http://purl.tuc.gr/dl/dias/C48AC57E-215D-43CB-A2FF-D7104F60B34E | ||
| Έτος | 2018 | ||
| Τύπος | Κεφάλαιο σε Βιβλίο | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | G. Chalkiadakis, C. Akasiadis, N. Savvakis, T. Tsoutsos, T. Hoppe and F. Coenen "Providing a scientific arm to renewable energy cooperatives," in The Role of Exergy in Energy and the Environment, vol. 262, Green Energy and Technology, Cham: Springer-Verlag, 2018, pp. 717-731. doi: 10.1007/978-3-319-89845-2_51 https://doi.org/10.1007/978-3-319-89845-2_51 | ||
| Εμφανίζεται στις Συλλογές |
Renewable Energy-Supplying cooperatives (REScoops) are cooperatives of renewable energy producers and/or consumers, which are under formulation in the emerging European smart grid. Their emergence highlights the importance of proconsuming green energy and simultaneously puts forward principles such as energy democracy and self-consumption, assists the fight against energy poverty, and helps reduce GHG emissions. To this end, the incorporation of scientific and technological solutions into the REScoops’ everyday business and practices, is key for improving these practices and assessing their potential benefits, and as such for enabling them to deliver the maximum possible gains to their members and society at large. This chapter outlines three key axes of scientific research and solutions that can be used for REScoops, namely, (a) a statistical analysis, (b) an applied behavioural analysis, and (c) an artificial intelligence/machine learning one. Also presented are results and lessons learned from providing such solutions to European REScoops as part of the H2020 REScoop Plus project.
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