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The near-optimal feasible space of a renewable power system model

Neumann, Fabian; Brown, Tom

Models for long-term investment planning of the power system typically return a single optimal solution per set of cost assumptions. However, typically there are many near-optimal alternatives that stand out due to other attractive properties like social acceptance. Understanding features that persist across many cost-efficient alternatives enhances policy advice and acknowledges structural model uncertainties. We apply the modeling-to-generate-alternatives (MGA) methodology to systematically explore the near-optimal feasible space of a completely renewable European electricity system model. While accounting for complex spatio-temporal patterns, we allow simultaneous capacity expansion of generation, storage and transmission infrastructure subject to linearized multi-period optimal power flow. Many similarly costly, but technologically diverse solutions exist. Already a cost deviation of 0.5% offers a large range of possible investments. However, either offshore or onshore wind energy along with some hydrogen storage and transmission network reinforcement appear essential to keep costs within 10% of the optimum.

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Verlagsausgabe §
DOI: 10.5445/IR/1000123353
Veröffentlicht am 05.02.2021
DOI: 10.1016/j.epsr.2020.106690
Zitationen: 10
Zitationen: 13
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 01.2021
Sprache Englisch
Identifikator ISSN: 0378-7796
KITopen-ID: 1000123353
HGF-Programm 37.12.02 (POF IV, LK 01) Design,Operation & Digitalization of the Future Energy Grids
Erschienen in Electric power systems research
Verlag Elsevier
Band 190
Seiten Art.Nr. 106690
Nachgewiesen in Web of Science
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