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Titel:

Dynamic control strategies for a solar-ORC system using first-law dynamic and data-driven machine learning models

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Zheng Liu; Alessandro Romagnol; Paul Sapin; Christos Markides; Matthias Mersch
Abstract:
In this study, we developed and assessed the potential of dynamic control strategies for a domestic scale 1-kW solar thermal power system based on a non-recuperated organic Rankine cycle (ORC) engine coupled to a solar energy system. Such solar-driven systems suffer from part-load performance deterioration due to diurnal and inter-seasonal fluctuations in solar irradiance and ambient temperature. Real-time control strategies for adjusting the operating parameters of these systems have shown grea...     »
Herausgeber:
Technical University of Munich
Kongress- / Buchtitel:
Proceedings of the 6th International Seminar on ORC Power Systems
Ausrichter der Konferenz:
Technical University of Munich
Datum der Konferenz:
11.10.2021-13.10.2021
Verlag / Institution:
Technical University of Munich
Jahr:
2021
E-ISBN:
978-3-00-070686-8
Serien-ISSN:
2709-7609
Reviewed:
ja
Sprache:
en
Erscheinungsform:
WWW
Volltext / DOI:
doi:10.14459/2021mp1633138
CC-Lizenz:
by-sa, http://creativecommons.org/licenses/by-sa/4.0
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