a simplistic method for representing renewable gasses and

A simplistic method for representingrenewable gasses and fuels in an energysystems optimisation modelIda Græsted Jensen, Frauke Wiese, Rasmus BramstoftDepartment of Management Engineering, Systems Analysis

e-mail: [email protected]

DTU Management Engineering, Technical University of Denmark

Introduction Modelling of RE-gas Case study Results

Motivation for using renewable gas and fuels

Enhancing the usage of gas inthe Danish energy system

Flexibility for VariableRenewable Energy Integrationin the Nordic Energy System

www.Flex4RES.org

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Motivation for this study

High share of wind energy ⇒ need of alternative, renewable anddispatchable electricity sources

How can renewable gas and fuels be integrated in an energysystems model without increasing the running time of themodel too much?

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The energy systems model BalmorelI An energy systems model considering existing capacity and

including possibility to investI Focusing on the energy system. Here defined as the heat

and power sectorI Can be extended by inclusion of several add-ons

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Why is RE-gas a problem in Balmorel?

I Only modelling ofconversion of fuels toelectricity and heat

I No representation of gasinfrastructure

I Limited representation ofgeography to reducerunning time:

I 4 countries (DK, NO,SE, DE)

I 15 regions (DK: 2, NO:5, SE: 4, DE: 4)

I 35 areas (DK: 14, NO:7, SE: 10, DE: 4)

13

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OptiFlow (FutureGas)

I Generalised spatio-temporal network optimisation model

I Can be connected to Balmorel to model production of REgas and fuels

15 May 2017DTU Management Engineering, Technical University of Denmark

Methodology

1

Balmorel OptiFlow

Electricity balance

District heat balance

Optimisation min. z (Money)

Natural gas market

Background system

Available resources, fuel prices, etc.

Biofuel market

Electricitydemand

Bi-products

District heat demand

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OptiFlow: production of RE gas and fuels

Electrolysis

Storage

Methanation

Transport of

resourcesResources

Storage

Anaerobic digestion

El

Engine using biogas

El

Biogas upgrading

TG ‐FT biodiesel

Transport of

resourcesFT biodiesel

Resources

Engine using syngas

MethanolMethanol synthesis

Thermal gasification

Transport of

resources

Water‐gas‐shift

Gas

Heat

Methanation

2nd generation fermentation

TG ‐ FT‐SPK, Bio‐jet

Ethanol

Bio‐jet

Biogasoline

Heat

ResourcesElectricityHeatProduct gasBiogasHydrogenBio natural gasMethanolBiodieselEthanolBiogasolineBio‐jet

Transport of

resources

Transport of

resources

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OptiFlow: drawbacks

I More data needed:I Higher resolution of

geographical data togenerate meaningfulresults

I Location of resourcesalong withtransportation costs

I Data for all processesincluded

I Size of the model explodes(more on this later)

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The simplistic method: overview (Flex4RES)

Using the Balmorel model without Optiflow but includingadd-ons that allow:

I Combining natural gas with upgraded biogas and upgradedthermal gas in existing and new natural gas technologies

I Including production of hydrogen and use of it formethanation of biogas and thermal gas

I Including a common limit of the gasses to reflect theoverall potential of biogas and thermal gas, respectively

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The simplistic method: CombTechI Allowing natural gas technologies to combine:

I Natural gasI Biogas (anaerobic digestion) or gas from thermal

gasification upgraded by CO2-removal (BIOGAS UP andTHERMGAS UP)

I Biogas or gas from thermal gasification upgraded byhydrogen addition (BIOGAS H2 and THERMGAS H2)

CHP

CHP

CHP

CHP

CHP

Natural gas

Biogas up

Biogas H2

Thermal gas up

Thermal gas H2

El

Heat

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The simplistic method: CombTechI Allowing natural gas technologies to combine:

I Natural gasI Biogas (anaerobic digestion) or gas from thermal

gasification upgraded by CO2-removal (BIOGAS UP andTHERMGAS UP)

I Biogas or gas from thermal gasification upgraded byhydrogen addition (BIOGAS H2 and THERMGAS H2)

CHP

Natural gas

Biogas up

Biogas H2

Thermal gas up

Thermal gas H2

El

Heat

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The simplistic method: Hydrogen add-on

Electrolysis

Storage

“Biogas H2"

El

El

“Thermal gas H2”

Thermal gas H2

Heat

Heat

Hydrogen

Fuel cell

Biogas H2

Methanation

Conversion factor

SOEC Methanation

Conversion factor

Bio natural gas

Product gasBiogasHydrogen

ElectricityHeat

Inclusion of a hydrogen demand constraint (simplified):∑i∈IH2prod

pH2i ,t + pH2−unload

t − pH2−loadt

= dH2t +

∑i∈IH2cons

pfueli +∑

i∈IH2upgr

γi pfueli

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Electrolysis

Storage

“Biogas H2"

El

El


Thermal gas H2

Heat

Heat

Hydrogen

Fuel cell

Biogas H2

Methanation

Conversion factor

SOEC Methanation

Conversion factor

Bio natural gas


ElectricityHeat



t − pH2−load

t

= dH2t +

∑i∈IH2cons

pfueli +∑

i∈IH2upgr

γi pfueli

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Electrolysis

Storage

“Biogas H2"

El

El


Thermal gas H2

Heat

Heat

Hydrogen

Fuel cell

Biogas H2

Methanation

Conversion factor

SOEC Methanation

Conversion factor

Bio natural gas


ElectricityHeat



t − pH2−loadt

= dH2t +

∑i∈IH2cons

pfueli +∑

i∈IH2upgr

γi pfueli

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The simplistic method: Common limit

An add-on which can set maximum limits in a flexible fashion:∑f ∈Fmax,rel (l)

∑i∈I(f )

γipfueli ≤

∑f ∈Fmax (l)

CAPf ∀l ∈ L

Where

I L represents the limit under consideration

I Fmax(l) represents the fuels that has an upper bound

I Fmax ,rel(l) represents the fuels that has an upper boundand the related fuels

StrawThermal

gasThermal gas up

Straw

Biogas Biogas up Biogas H2Biogas Biogas up Biogas H2

Thermal gas H2 ≤

≤

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Comparison of models

OptiFlow Simple Base

Blocks of equations 149 100 71Blocks of variables 39 24 19Electricity systemHeating systemRE gas and fuel production ÷ ÷Hydrogen demand ( ) ÷Transport fuels demand ( ) ( )Transportation of biomass ÷ ÷

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Scenarios

We test:

I Countries: Denmark, Germany, Norway, and Sweden

I Year 2050

I 4 weeks per year

I 24 hours per week

I No CO2-emissions allowed

I Fixed usage of municipal waste

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Model runs

We test the simple version by running:

1 Balmorel with no add-ons

2 Balmorel with the simplistic method but with no hydrogendemand

3 Balmorel with the simplistic method with a flat hydrogendemand in Eastern Denmark (20 PJ/year)

3 Balmorel with the simplistic method with a varyinghydrogen demand in Eastern Denmark (20 PJ/year)

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Results: objective function

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Results: Fuel Consumption, No add-ons

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Results: Fuel Consumption, SimpleNoH2demand

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Results: Fuel Consumption, SimpleFlat and SimpleVar

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Conclusion

I We have developed a simple method for inclusion ofrenewable gasses in an energy systems model

I The method gives a smaller model than inclusion of theOptiFlow model

I We suggest to:I Run OptiFlow for each specific country with a large number

of areas in the model to obtain hydrogen demandsI Use the hydrogen demands of the countries in Balmorel

with the simplistic method to obtain the optimal solutionwithin a reasonable running time

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a simplistic method for representing renewable gasses and

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