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Long-Term Energy Systems Planning: Accounting for Short-Term Variability and Flexibility
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
2014 (English)In: Renewable Energy Integration: Practical Management of Variability, Uncertainty, and Flexibility in Power Grids, Elsevier, 2014, 215-225 p.Chapter in book (Other academic)Text
Abstract [en]

Limiting global climate change to +2 °C may require an increase of renewable electricity generation from a 20% share today to close to 50% by 2035, according to the International Energy Agency. As variable renewable electricity generation is expected to grow, so is the need for sufficient flexibility in power systems. This flexibility is required to be able to balance short-term variability in supply and demand while maintaining the system's reliable operation. Power system models are frequently applied to assess such operational issues. However, the focus of short-term balancing is commonly omitted in the long-term energy system models used to inform policy development.This chapter demonstrates the importance of considering such short-term balancing in long-term energy models in order to derive reliable power system configurations. It explains how reliability considerations are commonly considered in conventional energy system models and discusses the applied coarse temporal resolution. Further, it presents a selection of modelling approaches which address some of the short-comings of conventional models. It demonstrates that dispatch and capacity investments derived from long-term models may be significantly different if the system's short-term variability is not accounted for in sufficient detail. Policies based on such models may therefore support investments in technologies which do not provide the flexibility required to integrate increasing shares of variable generation.

Place, publisher, year, edition, pages
Elsevier, 2014. 215-225 p.
Keyword [en]
Energy system modelling, OSeMOSYS, Power system operation
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-181267DOI: 10.1016/B978-0-12-407910-6.00017-XScopusID: 2-s2.0-84942926501ISBN: 9780124081222OAI: oai:DiVA.org:kth-181267DiVA: diva2:903734
Note

QC 20160216

Available from: 2016-02-16 Created: 2016-01-29 Last updated: 2016-02-16Bibliographically approved

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