Carpe Diem: A Novel Approach to Select Representative Days for Long-Term Power System Models with High Shares of Renewable Energy Sources

28 Pages Posted: 13 Dec 2014

See all articles by Paul Nahmmacher

Paul Nahmmacher

Potsdam-Institut für Klimafolgenforschung (PIK)

Eva Schmid

Potsdam-Institut für Klimafolgenforschung (PIK)

Lion Hirth

Neon Neue Energieökonomik GmbH; Hertie School of Governance

Brigitte Knopf

Mercator Research Institute on Global Commons and Climate Change (MCC)

Date Written: December 11, 2014

Abstract

In order to explore scenarios on the future of power systems, a variety of numerical models have been developed. As the share of variable renewable energy sources, particularly wind and solar, is projected to significantly increase, accounting for their temporal and spatial variability becomes ever more important in developing sound long-term scenarios. Computational restrictions prevent many long-term power system models being developed with an hourly resolution; instead they use time slices that aggregate periods with similar load and renewable electricity generation levels. There is to date no reproducible and validated method to derive and select time slices for power system models with multiple fluctuating time series. In this paper, we present a novel and effective method that is easily applied to input data for all kinds of power system models. We utilize this procedure in the long-term power system model LIMES-EU and show that a small number of representative days developed in this way are sufficient to reflect the characteristic fluctuations of the input data. Alongside a validation of the method, we discuss the conditions under which seasonal differentiation, and the use of representative weeks instead of days, is necessary.

Keywords: power system modeling, variability, renewable energy sources, time slices

Suggested Citation

Nahmmacher, Paul and Schmid, Eva and Hirth, Lion and Knopf, Brigitte, Carpe Diem: A Novel Approach to Select Representative Days for Long-Term Power System Models with High Shares of Renewable Energy Sources (December 11, 2014). USAEE Working Paper No. 14-194, Available at SSRN: https://ssrn.com/abstract=2537072 or http://dx.doi.org/10.2139/ssrn.2537072

Paul Nahmmacher (Contact Author)

Potsdam-Institut für Klimafolgenforschung (PIK) ( email )

Telegrafenberg 31
Potsdam, Brandenburg 14473
Germany

Eva Schmid

Potsdam-Institut für Klimafolgenforschung (PIK) ( email )

Telegraphenberg
Potsdam, Brandenburg 14412
Germany

Lion Hirth

Neon Neue Energieökonomik GmbH ( email )

Karl-Marx-Platz 12
12043
Berlin, 12043
Germany

HOME PAGE: http://www.neon-energie.de

Hertie School of Governance ( email )

Friedrichstraße 180
Berlin, 10117
Germany

Brigitte Knopf

Mercator Research Institute on Global Commons and Climate Change (MCC) ( email )

Torgauer Straße 12-15
Berlin, 10829
Germany

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