Abstract
We consider the capacity and operations planning of a European energy supply system with a high share of renewable energy. Our model includes the energy sectors electricity, heat, and transportation and it considers numerous types of consumers and power generation, storage, and transformation technologies, which participate in these energy sectors. Given time series for the regional demands in each sector and the potential renewable production, the goal is to simultaneously optimize the strategic dimensioning and the hourly operation of all components in the system such that the overall costs are minimized.
In this paper, we propose a Lagrangian solution approach that decomposes the model into many independent unit-commitment-type problems by relaxing several coupling constrains. This allows us to compute high quality lower bounds quickly and, in combination with some problem tailored heuristics, globally valid solutions with less computational effort.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Belloni, A., Diniz Souto Lima, A.L., Piñeiro Maceira, M.E., Sagastizábal, C.A.: Bundle relaxation and primal recovery in unit commitment problems. The Brazilian case. Ann. Oper. Res. 120, 21–44 (2003)
Bley, A., Fischer, F., Hahn, P.: Decomposition techniques for large scale optimisation problems. In: Proceedings of the 1st WindAc Africa, Cape Town (2016)
Gerhardt, N., Sandau, F., Scholz, A., Hahn, H.: Interaktion EE-Strom, Wärme und Verkehr. Tech. Rep., Fraunhofer IEE (2015)
Gerhardt, N., Böttger, D., Trost, T., Scholz, A., Pape, C., Gerlach, A.K., Härtel, P., Ganal, I.: Analyse eines europäischen 95-Prozent-Klimaschutzszenarios über mehrere Wetterjahre. Tech. Rep., Fraunhofer IEE (2017)
Gerhardt, N., Ganal, I., Jentsch, M., Rodriguez, J., Stroh, K., Buchmann, E.K.: Entwicklung der Gebäudewärme und Rückkopplung mit dem Energiesystem in 95-Prozent THG-Klimazielszenarien. Tech. Rep., Fraunhofer IEE (2019)
Helmberg, C.: ConicBundle 0.3.11 (2011)
Helmberg, C., Kiwiel, K.: A spectral bundle method with bounds. Math. Program. 93, 173–194 (2002)
IBM ILOG CPLEX: IBM ILOG CPLEX 12.7, User’s Manual for CPLEX (2015)
Jentsch, M.: Potenziale von Power-to-Gas Energiespeichern. Ph.D. Thesis, University of Kassel (2014)
Lemaréchal, C.: Lagrangian relaxation. In: Computational Combinatorial Optimization, pp. 112–156. Springer, Berlin (2001)
Lemaréchal, C.: The omnipresence of Lagrange. Ann. Oper. Res. 153, 9–27 (2007)
MathWorks MATLAB: MATLAB R2017a (2017)
Pape, C., Gerhardt, N., Härtel, P., Scholz, A., Schwinn, R., Drees, T., Maaz, A., Sprey, J., Breuer, C., Moser, A., Sailer, F., Reuter, S., Müller, T.: Roadmap Speicher. Speicherbedarf für Erneuerbare Energien - Speicheralternativen - Speicheranreiz - Überwindung rechtlicher Hemmnisse. Tech. Rep., Fraunhofer IEE (2014)
Acknowledgements
This work has been supported by the German Federal Ministry for Economic Affairs and Energy (BMWi), Grant 0325879, Project PfadE 3.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Bley, A., Pape, A., Fischer, F. (2020). A Lagrangian Decomposition Approach to Solve Large Scale Multi-Sector Energy System Optimization Problems. In: Neufeld, J.S., Buscher, U., Lasch, R., Möst, D., Schönberger, J. (eds) Operations Research Proceedings 2019. Operations Research Proceedings. Springer, Cham. https://doi.org/10.1007/978-3-030-48439-2_30
Download citation
DOI: https://doi.org/10.1007/978-3-030-48439-2_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-48438-5
Online ISBN: 978-3-030-48439-2
eBook Packages: Business and ManagementBusiness and Management (R0)