Kyriakidis, Loukas und Mendez, Miguel Alfonso und Bähr, Martin (2023) A Hybrid algorithm based on Bayesian Optimization and Interior Point OPTimizer for Optimal Operation of Energy Conversion Systems. In: 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023, Seiten 1299-1310. 36TH INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS, 2023-06-25 - 2023-06-30, Las Palmas de Gran Canaria, Spanien. doi: 10.52202/069564-0118. ISBN 978-171387492-8.
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Kurzfassung
Optimization methods are essential to improve the operation of energy conversion systems including energy storage equipment and fluctuating renewable energy. Modern systems consist of many components, operating in a wide range of conditions and governed by nonlinear balance equations. Consequently, identifying their optimal operation (e.g. minimizing operational costs) requires solving challenging optimization problems, with the global optimum often hidden behind many local ones. In this work, we propose a hybrid method that advantageously combines Bayesian optimization (BO) and Interior Point OPTimizer (IPOPT). The BO is a global approach which exploits Gaussian process regression to build a surrogate model of the cost function to be optimized, while IPOPT is a local approach which uses quasi-Newton updates. The proposed BO-IPOPT combination allows leveraging the parameter space exploration of the BO with the quasi-Newton convergence of IPOPT once solution candidates are in the neighbourhood of an optimum. Using a challenging constrained test function, we test BO-IPOPT in accuracy, robustness and computational efficiency. Finally, we showcase the proposed hybrid method in the optimal operation of an industrial energy conversion system for renewable steam generation.
elib-URL des Eintrags: | https://elib.dlr.de/199648/ | ||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||
Titel: | A Hybrid algorithm based on Bayesian Optimization and Interior Point OPTimizer for Optimal Operation of Energy Conversion Systems | ||||||||||||||||
Autoren: |
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Datum: | 2023 | ||||||||||||||||
Erschienen in: | 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, ECOS 2023 | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Ja | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||
DOI: | 10.52202/069564-0118 | ||||||||||||||||
Seitenbereich: | Seiten 1299-1310 | ||||||||||||||||
ISBN: | 978-171387492-8 | ||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||
Stichwörter: | Nonlinear global optimization, Bayesian optimization, IPOPT, Hybrid method, Renewable steam generation | ||||||||||||||||
Veranstaltungstitel: | 36TH INTERNATIONAL CONFERENCE ON EFFICIENCY, COST, OPTIMIZATION, SIMULATION AND ENVIRONMENTAL IMPACT OF ENERGY SYSTEMS | ||||||||||||||||
Veranstaltungsort: | Las Palmas de Gran Canaria, Spanien | ||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
Veranstaltungsbeginn: | 25 Juni 2023 | ||||||||||||||||
Veranstaltungsende: | 30 Juni 2023 | ||||||||||||||||
Veranstalter : | ECOS 2023 | ||||||||||||||||
HGF - Forschungsbereich: | Energie | ||||||||||||||||
HGF - Programm: | Materialien und Technologien für die Energiewende | ||||||||||||||||
HGF - Programmthema: | Thermische Hochtemperaturtechnologien | ||||||||||||||||
DLR - Schwerpunkt: | Energie | ||||||||||||||||
DLR - Forschungsgebiet: | E SP - Energiespeicher | ||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | E - Dekarbonisierte Industrieprozesse | ||||||||||||||||
Standort: | Cottbus | ||||||||||||||||
Institute & Einrichtungen: | Institut für CO2-arme Industrieprozesse | ||||||||||||||||
Hinterlegt von: | Kyriakidis, Loukas | ||||||||||||||||
Hinterlegt am: | 13 Dez 2023 12:47 | ||||||||||||||||
Letzte Änderung: | 24 Apr 2024 21:00 |
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