2019

Generating spatiallyresolved energy carrier specific heat load profilesAndrej Guminski i.r.o. Christoph Pellinger14.02.2019

Background - XOS

Methodology

Results

Application

Conclusion and Outlook

2

Agenda

Background - XOS

Methodology

Results

Application

Conclusion and Outlook

3

Agenda

The value of flexibility in the context of European electricity market coupling and extreme technological, regulatory and social

developments

4

Key Data• Duration: 01/2018 – 12/2020

• Research Consortium:• FfE e.V., FfE GmbH • Agora Energiewende, TUM (IfE, ENS), KIT ITAS

• 9 Project Partner• www.ffe.de/en/xos

Targets

• Development and application of methods to investigate the value of flexibility in the field of tension between Supply and Demand

• Scenarios taking disruptive developments in European energy markets – Analysis of the impacts for Germany

• Modelling of the regionalized energy system and power markets

Background - XOS

Methodology

Results

Application

Conclusion and Outlook

5

Agenda

The methodological approach contains three steps

6

Space Heating Hot Water

Temporal Distribution

Daily Load via Degree Day Numbers

Gas-, NightStorage Heater-,

Heat Pump-Profile

Uniformly for everyDay

Gas-, Heat Pump-Profile

Applicationoriented energy

balance

SpatialDistribution

Heating Structure

Weighting via Yearly Degree Day

Numbers

Heating Structure

Other AppliancesCooking

Standard Load Profile H0

PopulationPopulation

FFE-Hourly Load Profile

Methodological approach to deduce energy carrier specific FEC for space heating and hot water on NUTS-3-level

7

Temperature data Yearly Degree Day Numbers

Share of heating systems within every

NUTS-3-region

Population on NUTS-3-levelPopulation statistics

Output

Heating structure

CalculationInput

Yearly FEC per energy carrier on NUTS-3-level

for space heating

Yearly FEC per energy carrier and

application

Application oriented energy balance on

NUTS-0-level

Yearly FEC per energy carrier on NUTS-3-level

for hot water

Deduction of the heating structure: datasources, their level of detail and the type of processing

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Country Level of detail Type of processing Source

Austria NUTS-3 Type 1 [6]

Belgium NUTS-1 Type 1 [7]

Czech Republic NUTS-3 Type 1 [8]

Denmark NUTS-3 Type 1 [9]

France LAU-1 Type 1 [10]

Hungary NUTS-3 Type 1 [11]

Italy NUTS-2 Type 1 [12]

Netherlands NUTS-3 Type 1 [13]

Norway NUTS-2 Type 2 [14]

Poland NUTS-3 Type 1 [15]

Sweden NUTS-3 Type 2 [16]

Switzerland NUTS-3 Type 1 [17]

Slowakia NUTS-0 Type 1 [18]

Slowenia NUTS-3 Type 1 [19]

United Kingdom LAU-1 Type 1 [20]

Preprocessing:• Spatial resolution < NUTS-3 distribution according to population

• Data gaps (1) No data for a region and specific year data is interpolated (2) EC known to be used from the energy are missing distributed uniformly according to the population.

Types of datasets:• Type 1: number of heating systems by energy

carrier set equal to the share of FEC.

• Type 2: FEC per EC without noting the application. Share of energy carrier used for other appliances than heating.

Processing

Example of raw data content: share of heating systems in Switzerland by energy carrier and NUTS-3-region, data from [17]

Clear differences in shares of heating systems among NUTS-3-regions can be identified 9

0

0,2

0,4

0,6

0,8

1

Oil Coal Gas Electricity Biomass Solarthermal District heating Geothermal

Background - XOS

Methodology

Results

Application

Conclusion and Outlook

10

Agenda

Geographical and temporal variations persist in the processed data

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Spatial and temporal variation in Switzerland

Background - XOS

Methodology

Results

Application

Conclusion and Outlook

12

Agenda

A scenario is defined which allows for the investigation of a radical shift

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Scenario • Purpose: Illustrate the application of the derived model, hence it is simple and generic• Substitution-Scenario:

• Oil fired heating systems are replaced by heat pumps (efficiency = 2,8)• Gas fired heating systems are repleaced by direct electrical heating (efficiency = 1)

Value • Allows for the investigation of radical regulatory measurement on the electricity grid in energy system analysis

Motivation • One regulatory measure taken in Denmark in recent years was banning the installation of oil-fired boilers and natural gas heating in new buildings from 1st of January 2013.

An index is created to investigate if spatial differences are going to be significant in this scenario

Differences in the heating structure can be seen. This will translate into spatial differences in electricity demand and peak load in the subsitution scenario 14

• Q: Consumption of heat supplies• Q: Average consumption of heat applications

Spatial differences on a map are hard to spot, but it is possible…

E.g. a comparison of Northern Ireland with the UK still shows differences in the energy carrier index 15

Energy carrier index

< 0.05

< 0.3

< 0.6

< 0.9

< 1.2

< 1.5

≥ 1.5

Gas index Oil index

´ Administrative boundaries: Europe: © 2018 Geofabrik GmbH and OpenStreetMap Contributors | Germany: © GeoBasis-DE / BKG 2017 | Generalization: FfE e.V.0 250 500125Kilometer

Energy carrier index for oil and gas

Results yield an increase of up to more than 600 % in peak load and 400 % in electricity consumption of private households

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00 250 500125

Kilometer´ Administrative boundaries: Europe: © 2018 Geofabrik GmbH and OpenStreetMap Contributors | Germany: © GeoBasis-DE / BKG 2017 | Generalization: FfE e.V.

Relative change of peak load in %

≤ 100

≤ 200

≤ 300

≤ 400

≤ 500

≤ 600

> 600

Comparison between increasing consumption and

peak load in all NUTS-3-regions

Relative change of peak load of private households on NUTS-3-

level

Significant differences of change in peak load in countries with similar ratios of electricity consumption before and after substitution can be explained by different climate conditions

17

0

10

20

30

40

50

60

70

80

90

0 2000 4000 6000 8000

load

[GW

]

hour of the year

IT

0

10

20

30

40

50

60

70

80

90

0 2000 4000 6000 8000

load

[GW

]

hour of the year

UK

3,14 350 % 3,39 600 %

Background - XOS

Methodology

Results

Application

Conclusion and Outlook

18

Agenda

Conclusion Outlook− Metohodology and data are available for the

calculation of spatially resolved heat load profiles − The methodology allows for a differentiation in

energy carriers and technologies− The analyses of the scenario show strong spatial

differences in the peak load of private households within a country

− This proves that a resolution at NUTS-3-level is necessary for energy system analysis, which consider the electrical transmission grid

+ Compare the change in electrical energy consumption not only to the consumption of private household.

+ Refine the model with more country specific input data

+ Model the implications of renovation and demography

+ Do the same type of modelling for other sectors+ …ideas?

Conclusion and Outlook

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?!„…“

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Thank you for your attention!

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Questions? Suggestions?

Further Proceeding?

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Discussion

Forschungsstelle für Energiewirtschaft e. V.Am Blütenanger 7180995 MünchenTel.: +49(0)89 15 71 21 – 0Email: info@ffe.deInternet: www.ffe.deTwitter: @FfE_Muenchen

Christoph PellingerLeitung strategische ProjektplanungForschungsstelle für Energiewirtschaft e.V.Tel.: +49(0)89 15 71 21 – 70Email: cpellinger@ffe.de