Consideration of disruptive elements in energy system models -Findings from the RegMex project

1. Consideration of disruptive elements in energy
system models - Findings from the RegMex project
IRENA/IEA Workshop „Understanding Innovation“
09.11.2018, Stuttgart
Hans Christian Gils
DLR Energy Systems Analysis

2. • Definition of a standardized scenario framework for two model experiments
• Development of templates for increasing comparability of models and data
• Implementation of the model experiments and derivation of robust conclusions
• Evaluation of disruptive elements and their representation in energy models
Goals of the “RegMex“ project
Project consortium:
DLR.de • Chart 2 > IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

3. Model experiments
DLR.de • Chart 3
1. Overall energy system 2. Enhanced power system
Focus Transformation pathways Load balancing (storage, grid,
DSM, flexible sector integration)
Geographical coverage Germany Germany, 18 regions
Investigation period/year 2015-2050 2050
Temporal resolution Representative days / hourly Hourly
Sectoral coverage All energy usage Power, links to heat/transport
Participating models REMod-D (Fraunhofer ISE)
TIMES PanEU (IER)
SCOPE (Fraunhofer IEE)
REMix (DLR)
PowerFlex (Öko Institute)
SCOPE (Fraunhofer IEE)
ELMOD (TU Dresden)
Scenarios Differing in CO2 reduction
(80% vs. 90% to 1990)
Differing in RE supply and grid
infrastructures, driven by
exogenous domestic generation
share and option of endogenous
grid expansion
> IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

4. • Differences in input data cause significant deviations in some results
• Strong increase in power demand due to electrification of other sectors
• Wind and PV are main pillars of energy supply in 2050
• Increasing demand for back-up generation capacity
Main results of model experiment 1
DLR.de • Chart 4
0
100
200
300
400
500
REMod-D
TIMES
PanEU
SCOPE
REMod-D
TIMES
PanEU
SCOPE
GWel
Laufwasser-KW
Wind Offshore
Wind Onshore
PV
2030 2050
> IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

5. • Identical parameterization leads to approximation of results
• Considerable demand for temporal balancing on all time scales
• Demand flexibility of H2 electrolysis, electric heating and BEV charging can
complement and replace power transmission and storage
• Flexible sector integration particularly important when grid extension is limited
Main results of model experiment 2
DLR.de • Chart 5
Total generation and grid usage Temporal balancing
> IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

6. Disruptive elements – collection and evaluation
DLR.de • Chart 6
Collection of potentially disruptive elements
Definition: Disruptive elements are events that are a significant deviation from
current trends, and that have major impact on the energy system transformation
> IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

7. • Extremely fast implementation of Industry 4.0
• Massive cost reductions of decentralized storage
• Massive CCS cost reductions
• Smart Grid, Smart Markets, Smart Homes, Smart…
• Close to zero power costs, flat rate
• Electricity/energy autarchic buildings
• Increasing residential/commercial demand due to own production (3D printers)
• Break-through of completely new power generation technologies
Disruptive elements related to technology innovation
DLR.de • Chart 7 > IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

8. Disruptive elements – feasibility of model implementation
DLR.de • Chart 8
Disruptive element 1 2 3 4 5 6 Count
Global energy markets (e.g. increase in fuel prices) 5
High real interest rate 5
Prolonged economic downturn 3
No/reduced international power exchange 5
No/reduced availability of gas imports 4
Massive cost reductions of decentralized storage 5
Massive CCS cost reductions 3
Reduced RE technology learning rates 4
Dismantling of gas networks 0
No acceptancy 3
Climate change impact on power generation 2
Reduced power supply security 2
Delayed / limited grid expansion 3
Failure of electrification strategy 5
Shortage or cost explosion of structural materials 1
Reduced biomass availability to the energy sector 5
Smart Grid, Smart Markets, Smart Homes, Smart… 2
Temporal turnaround in national energy policy 3
Inacceptable costs of climate policy 2
Close to zero power costs, flat rate 3
Change in consumer behaviour 4
Yes
No
Partially
> IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

9. Adjustments required to model disruptions
Disruptive element Adjustment 1 Adjustment 2 Count
High real interest rate
Cost parameter
5
Massive cost reductions of decentralized storage 5
Global energy markets (e.g. increase in fuel prices) 5
No/reduced availability of gas imports
Technology parameter
4
Reduced RE technology learning rates 4
Close to zero power costs, flat rate Demand 3
Temporal turnaround in national energy policy 3
Shortage or cost explosion of structural materials 1
Dismantling of gas networks Demand 0
Reduced power supply security Modelling approach 2
Change in consumer behaviour
Demand
4
Prolonged economic downturn
Climate change impact on power generation 2
Smart Grid, Smart Markets, Smart Homes, Smart… Technology parameter 2
Inacceptable costs of climate policy 2
No/reduced international power exchange
Technology parameter
5
Failure of electrification strategy Demand 5
Reduced biomass availability to the energy sector 5
Massive CCS cost reductions Cost parameter 3
No acceptancy 3
Delayed / limited grid expansion 3
DLR.de • Chart 9 > IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

10. • In the optimization of transformation pathways with disruptions an approach
with partial foresight and rolling horizon appears most suited
• Potential combination with stochastic modelling approaches, e.g. focused on
technology innovation
Modelling disruptive elements – model horizon
DLR.de • Chart 10 > IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

11. • Almost all disruptions identified can be implemented in at least one model
• Mostly possible by adjustment of demand, cost or technology parameter
• Foresight over full planning horizon not compatible with analysis of disruptions
Summary
DLR.de • Chart 11 > IRENA/IEA Workshop „Understanding Innovation“ > Hans Christian Gils • Findings from the RegMex project > 9 November 2018

12. 12
Contact:
Dr. Hans Christian Gils
German Aerospace Center (DLR)
Institute of Engineering Thermodynamics
Energy Systems Analysis Department
Pfaffenwaldring 38-40 | 70569 Stuttgart | Germany
Phone +49 711 6862-477 | Fax +49 711 6862-747
hans-christian.gils@dlr.de
www.DLR.de/tt
This presentation relies on the final report of the RegMex project:
Lechtenböhmer, S.; Palzer, A.; Pregger, T.; Gils, H.C.; Sterchele, P.; Kost, C.; Brucker, L.; Janßen, T.;
Krüger, C.; Schüwer, D.; Luhmann, H.-J.; Buddeke, M. (2018): RegMex - Modellexperimente und
Vergleiche zur Simulation von Wegen zu einer vollständig regenerativen Energieversorgung.
https://elib.dlr.de/121339/

13. > Lecture > Author • Document > DateDLR.de • Chart 13
Nr. Nr. Kurzname
1 Einflüsse globaler Energiemärkte
2 Makroökonomische Einflüsse
2a hohe Realzinsen
2b hohe Inflation
2c langanhaltende Rezession
2d Finanzknappheit
2e stärkeres Wirtschaftswachstum
3 Splittung des Europäischen Marktes
3a s. makroökonomische Effekte
3b s. kein Stromaustausch
4 Kein (Strom-)Austausch
5 Erdgasverfügbarkeit sinkt
6 Sehr schnelle Verbreitung von Industrie 4.0
7 Variation der Stromgestehungskosten/-speicher/Smart … durch Technologieweiterentwicklungen
8 Kostendurchbruch dezentrale Speicher
9 Kostendurchbruch CCS
10 Stromerzeugung kostet kurzfristig nichts mehr, Flatrate-Tarife…
11 Geringe Lerneffekte bei EE-Technologien
12 Langsamer Ausbau von EE-Technologien
13 Rückbau Gasnetz
14 Zielverfehlung bei Einsparzielen
15 Gesellschaftliche Risiken
15a Keine Akzeptanz
15b Demographische Entwicklung
15c Konsumentenverhalten

14. > Lecture > Author • Document > DateDLR.de • Chart 14
Nr. Nr. Kurzname
16 Klimapolitik der Bundesländer und Kommunen
17 Auswirkungen Klimawandel auf Energiewirtschaft
18 Versorgungssicherheit Strom sinkt
19 Netzausbau findet nicht in erwartetem Maße statt
20 Elektrifizierungsstrategie kann nicht umgesetzt werden
21 Technische Risiken der Umstellung des Energiesystems auf Strom
22 Lock-in-Situationen
23 Verknappungen/Preisanstieg von Strukturmaterialien
24 Engpässe bei energetischen Biomassenutzung
25 Smart Grid, Smart Markets, Smart Homes, Smart…
26 Ziel Energiewende wird im Bund für 1 Legislaturperiode nicht verfolgt
27 Wirkung ungleicherer Einkommensverteilung auf das Energiesystem
28 Strom(energie)autarke Häuser
29 Infrastruktur für Bahngüterverkehr wird schlechter
30 Regionaler Luftgüterverkehr
31 Eigenproduktion HH, GHD steigt (3D-Drucker)
32 Einschlägige Gesetze verfehlen Wirkung
33 Reaktion auf erhöhte Gefahr kurzfristiger Unterbrechungen (z. B. Terroranschläge)
34 Exotische Stromerzeugungssysteme setzen sich durch (z. B. Nutzung piezoelektrischer Effekte)
35 Personenverkehr
35 a Verhalten: PKW-Nutzung bleibt dominant, Verkehrsleistung sinkt kaum
35 b Elektrifizierung (auch indirekte) unterbleibt; ggf. Biomasseverfügbarkeit eingeschränkt
36 Unakzeptable Kosten der Klimapolitik
37 Naturkatastrophen - Man-made