2018-01-24T07:41:57Z

Philipp Hauser:

= Introduction =

Here datasets and modelling issues for the long-distance transport of natural gas are listed.

= Gas network datasets by region =

== Germany ==

[https://www.bdew.de/internet.nsf/id/8DFFSL-DE_Grafiken BDEW maps]

[http://www.diw.de/sixcms/detail.php?id=diw_01.c.574115.de DIW Data Documentation 92] "Electricity, Heat and Gas Sector Data for Modelling the German System"

[http://www.bundesnetzagentur.de/DE/Sachgebiete/ElektrizitaetundGas/Unternehmen_Institutionen/NetzentwicklungundSmartGrid/Gas/NEP_Gas2016/NEP_Gas2016_node.html German Network Development Plan (NEP) for Gas 2016-2026]

[https://dokumente.ub.tu-clausthal.de/servlets/MCRFileNodeServlet/Document_derivate_00000154/Db112168.pdf PhD Thesis of Jessica Rövekamp] contains German data

 

 

== Europe ==

 

=== Natural Gas Demand ===

ToDo

=== Natural Gas Supply ===

ToDo

 

=== Natural Gas Infrastructure ===

[http://www.gie.eu/ Gas Infrastructure Europe] 

[http://www.entsog.eu/maps/transmission-capacity-map ENTSO-G capacities and maps] 

[http://www.vge.de/wandkarten.aspx VGE European and German gas maps]

==== Pipelines ====

ToDo

==== LNG ====

ToDo

==== Storages ====

ToDo

 

 

 

= Modelling issues =

Compressibility, line pack (i.e. storage inside pipes), gas consumption of compressors, daily modelling, Gross Calorific Value (GCV), storage, LNG transport

Compressors are needed to maintain pressure throughout the network. They are typically stationed every 90 km to 150 km in the long-distance network, sometimes up to every 400 km for international routes [Rövekamp]. Onshore long-distance pipelines have a diameter of 0.4 to 1.4 meters and pressures up to 100 bar [Rövekamp]. The compressors can consume up to 5-10% of the transported gas (0.3% per 150 km? citation needed).

It's apparently hard to measure exactly what is flowing at any one time in the network; often only daily flows are modelled or reported.

The [http://petrowiki.org/Pressure_drop_evaluation_along_pipelines#Weymouth_equation Weymouth equation] is an approximation used to calculate the flow in the pipe based on the pressures at either end. It is generally used for high-Reynolds-number flows where the Moody friction factor is merely a function of relative roughness.

The relation between pressures p_{m,n} at m,n and flow f_{mn} is given by:

f_{mn} = sgn(p_m,p_n) C_{mn} \sqrt{|p_m^2 - p_n^2|}

where sgn(p_m,p_n) =1 if p_m \geq p_n and sgn(p_m,p_n) = -1 if p_m < p_n.

 

= List of Gas Models =

*COLUMBUS
*[[GAMAMOD|GAMAMOD]]
*GAMMES
*GASTALE
*NATGAS
*S-GASTALE
*TIGER
*WGM (The World Gas Model)

= Publications =

== Gas Network Modelling ==

*European Climate Foundation [https://europeanclimate.org/energy-union-choices-a-perspective-on-infrastructure-and-energy-security-in-the-transition/ Energy Union Choices: A Perspective on Infrastructure and Energy Security in the Transition], Report, 2016 
*Geidl, M. and Andersson G. [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.164.5417&rep=rep1&type=pdf Optimal Power Flow of Multiple Energy Carriers] IEEE Transactions on Power Systems, 22(1), 2007
*Hauser, P.; Hobbie, H.; Möst, D. [http://ieeexplore.ieee.org/document/7981942/ Resilience in the German Natural Gas Network: Modelling Approach for a High-Resolution Natural Gas System]''',''' 14th International Conference on the European Energy Market, IEEE Xplore
*Kunz, F.; Kendziorski, M.; Schill, W.; Weibezahn, J.; Zepter, J. von Hirschhausen, C.; Hauser, P.; Zech, M.; Möst, D.; Heidari, S.; Felten, J.; Weber, C.: [http://www.diw.de/sixcms/detail.php?id=diw_01.c.574115.de Electricity, Heat and Gas Sector Data for Modelling the German System], Data Documentation, 2017
*Neumann, A., Rosellón, J. & Weigt, H. [http://link.springer.com/article/10.1007/s11067-014-9273-3 Removing Cross-Border Capacity Bottlenecks in the European Natural Gas Market—A Proposed Merchant-Regulatory Mechanism] Networks and Spatial Economics, March 2015, Volume 15, Issue 1, pp 149–181, [https://www.diw.de/documents/publikationen/73/diw_01.c.376700.de/dp1145.pdf DIW Working Paper]
*Rövekamp, J. [https://dokumente.ub.tu-clausthal.de/servlets/MCRFileNodeServlet/Document_derivate_00000154/Db112168.pdf Transportnetzberechnung zur Feststellung der Erdgasversorgungssicherheit in Deutschland unter regulatorischem Einfluss] - PhD Thesis, 2014, TU Clausthal - the references give a good literature overview 

 

== Linearised Weymouth equations ==

*Kjetil T. Midthun, Mette Bjørndal and Asgeir Tomasgard [http://www.jstor.org/stable/41323248 Modeling Optimal Economic Dispatch and System Effects in Natural Gas Networks], The Energy Journal, Vol. 30, No. 4 (2009), pp. 155-180

 

 

== Coupling gas-electricity ==

*<references />Abrell, J., Gerbaulet, C., Holz, F., Lorenz, C., and Weigt, H. [http://www.diw.de/documents/publikationen/73/diw_01.c.425843.de/dp1317.pdf Combining Energy Networks The Impact of Europe's Natural Gas Network on Electricity Markets until 2050], 2013 DIW Working Paper 
*<references />Abrell, J., Weigt, H. [https://wwz.unibas.ch/uploads/tx_x4epublication/Combined_dynamic_Abrell_Weigt_2014.05.pdf Investments in a Combined Energy Network Model: Substitution between Natural Gas and Electricity] WWZ Discussion Paper 2014/05 
*<references />Arnold, M. and Andersson, G. [https://www.eeh.ee.ethz.ch/uploads/tx_ethpublications/Arnold_DecomposedElectricityandNaturalGasOPF.pdf Decomposed Electricity and Natural Gas Optimal Power] 
*<references />Hürrenrauch et al. (2017) 
*<references />McCalley, J. (2015) [http://iiesi.org/assets/pdfs/iiesi_102_mccalley1.pdf Integrated Energy System: Co-optimization & Design Issues (Presentation)] 
*<references />McCalley, J. (2015) [http://iiesi.org/assets/pdfs/101_mccalley_2.pdf Gas-Electricity Nexus (Presentation)]

Gas network datasets

2018-01-24T07:35:07Z

Philipp Hauser:

= Introduction =

Here datasets and modelling issues for the long-distance transport of natural gas are listed.

= Gas network datasets by region =

== Germany ==

[https://www.bdew.de/internet.nsf/id/8DFFSL-DE_Grafiken BDEW maps]

[http://www.diw.de/sixcms/detail.php?id=diw_01.c.574115.de DIW Data Documentation 92] "Electricity, Heat and Gas Sector Data for Modelling the German System"

[http://www.bundesnetzagentur.de/DE/Sachgebiete/ElektrizitaetundGas/Unternehmen_Institutionen/NetzentwicklungundSmartGrid/Gas/NEP_Gas2016/NEP_Gas2016_node.html German Network Development Plan (NEP) for Gas 2016-2026]

[https://dokumente.ub.tu-clausthal.de/servlets/MCRFileNodeServlet/Document_derivate_00000154/Db112168.pdf PhD Thesis of Jessica Rövekamp] contains German data

 

 

== Europe ==

 

=== Natural Gas Demand ===

ToDo

=== Natural Gas Supply ===

ToDo

 

=== Natural Gas Infrastructure ===

[http://www.gie.eu/ Gas Infrastructure Europe] 

[http://www.entsog.eu/maps/transmission-capacity-map ENTSO-G capacities and maps] 

[http://www.vge.de/wandkarten.aspx VGE European and German gas maps]

==== Pipelines ====

ToDo

==== LNG ====

ToDo

==== Storages ====

ToDo

 

 

 

= Modelling issues =

Compressibility, line pack (i.e. storage inside pipes), gas consumption of compressors, daily modelling, Gross Calorific Value (GCV), storage, LNG transport

Compressors are needed to maintain pressure throughout the network. They are typically stationed every 90 km to 150 km in the long-distance network, sometimes up to every 400 km for international routes [Rövekamp]. Onshore long-distance pipelines have a diameter of 0.4 to 1.4 meters and pressures up to 100 bar [Rövekamp]. The compressors can consume up to 5-10% of the transported gas (0.3% per 150 km? citation needed).

It's apparently hard to measure exactly what is flowing at any one time in the network; often only daily flows are modelled or reported.

The [http://petrowiki.org/Pressure_drop_evaluation_along_pipelines#Weymouth_equation Weymouth equation] is an approximation used to calculate the flow in the pipe based on the pressures at either end. It is generally used for high-Reynolds-number flows where the Moody friction factor is merely a function of relative roughness.

The relation between pressures p_{m,n} at m,n and flow f_{mn} is given by:

f_{mn} = sgn(p_m,p_n) C_{mn} \sqrt{|p_m^2 - p_n^2|}

where sgn(p_m,p_n) =1 if p_m \geq p_n and sgn(p_m,p_n) = -1 if p_m < p_n.

 

= Publications =

== Gas Network Modelling ==

*European Climate Foundation [https://europeanclimate.org/energy-union-choices-a-perspective-on-infrastructure-and-energy-security-in-the-transition/ Energy Union Choices: A Perspective on Infrastructure and Energy Security in the Transition], Report, 2016 
*Geidl, M. and Andersson G. [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.164.5417&rep=rep1&type=pdf Optimal Power Flow of Multiple Energy Carriers] IEEE Transactions on Power Systems, 22(1), 2007
*Hauser, P.; Hobbie, H.; Möst, D. [http://ieeexplore.ieee.org/document/7981942/ Resilience in the German Natural Gas Network: Modelling Approach for a High-Resolution Natural Gas System]''',''' 14th International Conference on the European Energy Market, IEEE Xplore
*Kunz, F.; Kendziorski, M.; Schill, W.; Weibezahn, J.; Zepter, J. von Hirschhausen, C.; Hauser, P.; Zech, M.; Möst, D.; Heidari, S.; Felten, J.; Weber, C.: [http://www.diw.de/sixcms/detail.php?id=diw_01.c.574115.de Electricity, Heat and Gas Sector Data for Modelling the German System], Data Documentation, 2017
*Neumann, A., Rosellón, J. & Weigt, H. [http://link.springer.com/article/10.1007/s11067-014-9273-3 Removing Cross-Border Capacity Bottlenecks in the European Natural Gas Market—A Proposed Merchant-Regulatory Mechanism] Networks and Spatial Economics, March 2015, Volume 15, Issue 1, pp 149–181, [https://www.diw.de/documents/publikationen/73/diw_01.c.376700.de/dp1145.pdf DIW Working Paper]
*Rövekamp, J. [https://dokumente.ub.tu-clausthal.de/servlets/MCRFileNodeServlet/Document_derivate_00000154/Db112168.pdf Transportnetzberechnung zur Feststellung der Erdgasversorgungssicherheit in Deutschland unter regulatorischem Einfluss] - PhD Thesis, 2014, TU Clausthal - the references give a good literature overview 

 

== Linearised Weymouth equations ==

*Kjetil T. Midthun, Mette Bjørndal and Asgeir Tomasgard [http://www.jstor.org/stable/41323248 Modeling Optimal Economic Dispatch and System Effects in Natural Gas Networks], The Energy Journal, Vol. 30, No. 4 (2009), pp. 155-180

 

 

== Coupling gas-electricity ==

*<references />Abrell, J., Gerbaulet, C., Holz, F., Lorenz, C., and Weigt, H. [http://www.diw.de/documents/publikationen/73/diw_01.c.425843.de/dp1317.pdf Combining Energy Networks The Impact of Europe's Natural Gas Network on Electricity Markets until 2050], 2013 DIW Working Paper 
*<references />Abrell, J., Weigt, H. [https://wwz.unibas.ch/uploads/tx_x4epublication/Combined_dynamic_Abrell_Weigt_2014.05.pdf Investments in a Combined Energy Network Model: Substitution between Natural Gas and Electricity] WWZ Discussion Paper 2014/05 
*<references />Arnold, M. and Andersson, G. [https://www.eeh.ee.ethz.ch/uploads/tx_ethpublications/Arnold_DecomposedElectricityandNaturalGasOPF.pdf Decomposed Electricity and Natural Gas Optimal Power] 
*<references />Hürrenrauch et al. (2017) 
*<references />McCalley, J. (2015) [http://iiesi.org/assets/pdfs/iiesi_102_mccalley1.pdf Integrated Energy System: Co-optimization & Design Issues (Presentation)] 
*<references />McCalley, J. (2015) [http://iiesi.org/assets/pdfs/101_mccalley_2.pdf Gas-Electricity Nexus (Presentation)]

Gas network datasets

2018-01-23T14:30:27Z

Philipp Hauser: /* Coupling gas-electricity */

Gas network datasets

2018-01-23T09:42:37Z

Philipp Hauser: /* Europe */

Gas network datasets

2018-01-23T09:41:40Z

Philipp Hauser:

Technische Universität Dresden (EE2)

2018-01-23T09:39:05Z

Philipp Hauser: /* Used Models */

{{Institution
|Full Name=Technische Universität Dresden, Chair of Energy Economics
|Abbreviation=TUD EE2
|Website=https://tu-dresden.de/bu/wirtschaft/ee2
|Address=Münchnerplatz 3, 01062 Dresden
|Email=ee2@mailbox.tu-dresden.de
}}
Research at the Chair of Energy Economics at the Technische Universität Dresden addresses techno-economic questions along the entire energetic value chain, starting from primary energy production via energy conversion and transport to the final energy usage. We mainly focus on analyzing the development of European electricity and gas markets, the integration of renewable sources as well as energy and resource efficiency.

= Used Models =

*ELMOD (EE2)
*ELTRAMOD
*[[GAMAMOD|GAMAMOD]]

= Conferences =

*ENERDAY
*EEM 2017

GAMAMOD

2018-01-23T09:37:51Z

Philipp Hauser:

{{Model
|Full_Model_Name=Gas Market Model
|Acronym=GAMAMOD
|author_institution=Technische Universität Dresden (EE2)
|authors=Philipp Hauser
|contact_persons=Philipp Hauser
|contact_email=philipp.hauser@tu-dresden.de
|website=https://tu-dresden.de/bu/wirtschaft/ee2/forschung/modelle/gamamod?set_language=en
|text_description=The gas market model GAMAMOD is a bottom-up model used to determine and analyse the optimal natural gas supply structure in Europe and to examine the utilization of the natural gas infrastructure. In its basic version, the model includes the EU-28 countries as well as Switzerland, Norway, the Baltic States and the Balkan region. In addition, important suppliers for the European natural gas market are considered (e.g. Russia, Algeria, and Qatar). On the supply side, the model considers different production capacities with respect to the production level. The model enables the transport of natural gas by modelling pipelines and liquefied natural gas (LNG) shipping. The capacity of single pipelines between neighbouring countries are aggregated in the model. In the case of LNG shipping, the model considers regasification and liquefaction capacities in export and import countries. The model includes an exogenously imputed natural gas demand for each respective country. Moreover, seasonal demand patterns in the respective countries are considered.
GAMAMOD enables the analysis of trading capacities between regional markets. Due to restricted transmission capacities, regional incidences of congestions might occur. The model allows for examining supply interruptions and their impact on the European natural gas system. As each country is modelled as a single aggregated node, no congestions occur within a market area. Furthermore, the model considers natural gas storage, which ensures security of supply in the European natural gas market.
Cyprus and Malta are isolated from the integrated European natural gas pipeline grid. Therefore, they are not considered in the model.
|open_source_licensed=No
|model_source_public=No
|data_availability=some
|open_future=Yes
|modelling_software=GAMS
|GUI=No
|model_class=European Natural Gas Market
|sectors=gas
|Demand sectors=Households, Industry, Other
|Energy carrier (Gas)=Natural gas, Biogas, Hydrogen
|Transfer (Electricity)=Distribution
|Transfer (Gas)=Distribution, Transmission
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|network_coverage=transmission, distribution
|Observation period=Less than one month
|math_modeltype=Optimization
|is_suited_for_many_scenarios=No
|montecarlo=No
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

GAMAMOD

2018-01-23T09:35:39Z

Philipp Hauser: Created page with "{{Model |Full_Model_Name=Gas Market Model |Acronym=GAMAMOD |author_institution=TU Dresden, (EE2) |authors=Philipp Hauser |contact_persons=Philipp Hauser |contact_email=philipp..."

{{Model
|Full_Model_Name=Gas Market Model
|Acronym=GAMAMOD
|author_institution=TU Dresden, (EE2)
|authors=Philipp Hauser
|contact_persons=Philipp Hauser
|contact_email=philipp.hauser@tu-dresden.de
|website=https://tu-dresden.de/bu/wirtschaft/ee2/forschung/modelle/gamamod?set_language=en
|text_description=The gas market model GAMAMOD is a bottom-up model used to determine and analyse the optimal natural gas supply structure in Europe and to examine the utilization of the natural gas infrastructure. In its basic version, the model includes the EU-28 countries as well as Switzerland, Norway, the Baltic States and the Balkan region. In addition, important suppliers for the European natural gas market are considered (e.g. Russia, Algeria, and Qatar). On the supply side, the model considers different production capacities with respect to the production level. The model enables the transport of natural gas by modelling pipelines and liquefied natural gas (LNG) shipping. The capacity of single pipelines between neighbouring countries are aggregated in the model. In the case of LNG shipping, the model considers regasification and liquefaction capacities in export and import countries. The model includes an exogenously imputed natural gas demand for each respective country. Moreover, seasonal demand patterns in the respective countries are considered.
GAMAMOD enables the analysis of trading capacities between regional markets. Due to restricted transmission capacities, regional incidences of congestions might occur. The model allows for examining supply interruptions and their impact on the European natural gas system. As each country is modelled as a single aggregated node, no congestions occur within a market area. Furthermore, the model considers natural gas storage, which ensures security of supply in the European natural gas market.
Cyprus and Malta are isolated from the integrated European natural gas pipeline grid. Therefore, they are not considered in the model.
|open_source_licensed=No
|model_source_public=No
|data_availability=some
|open_future=Yes
|modelling_software=GAMS
|GUI=No
|model_class=European Natural Gas Market
|sectors=gas
|Demand sectors=Households, Industry, Other
|Energy carrier (Gas)=Natural gas, Biogas, Hydrogen
|Transfer (Electricity)=Distribution
|Transfer (Gas)=Distribution, Transmission
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|network_coverage=transmission, distribution
|Observation period=Less than one month
|math_modeltype=Optimization
|is_suited_for_many_scenarios=No
|montecarlo=No
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

2018-01-17T08:14:47Z

Philipp Hauser: /* Germany */

= Introduction =

Here datasets and modelling issues for the long-distance transport of natural gas are listed.

 

= Gas network datasets by region =

== Germany ==

[http://http://www.diw.de/sixcms/detail.php?id=diw_01.c.574115.de DIW Data Documentation 92] "Electricity, Heat and Gas Sector Data for Modelling the German System"

== Europe ==

[http://www.gie.eu/ Gas Infrastructure Europe]

[http://www.entsog.eu/maps/transmission-capacity-map ENTSO-G capacities and maps]

[http://www.bundesnetzagentur.de/DE/Sachgebiete/ElektrizitaetundGas/Unternehmen_Institutionen/NetzentwicklungundSmartGrid/Gas/NEP_Gas2016/NEP_Gas2016_node.html German Network Development Plan (NEP) for Gas 2016-2026]

[http://www.vge.de/wandkarten.aspx VGE European and German gas maps]

[https://www.bdew.de/internet.nsf/id/8DFFSL-DE_Grafiken BDEW maps]

[https://dokumente.ub.tu-clausthal.de/servlets/MCRFileNodeServlet/Document_derivate_00000154/Db112168.pdf PhD Thesis of Jessica Rövekamp] contains German data

 

= Modelling issues =

Compressibility, line pack (i.e. storage inside pipes), gas consumption of compressors, daily modelling, Gross Calorific Value (GCV), storage, LNG transport

Compressors are needed to maintain pressure throughout the network. They are typically stationed every 90 km to 150 km in the long-distance network, sometimes up to every 400 km for international routes [Rövekamp]. Onshore long-distance pipelines have a diameter of 0.4 to 1.4 meters and pressures up to 100 bar [Rövekamp]. The compressors can consume up to 5-10% of the transported gas (0.3% per 150 km? citation needed).

It's apparently hard to measure exactly what is flowing at any one time in the network; often only daily flows are modelled or reported.

The [http://petrowiki.org/Pressure_drop_evaluation_along_pipelines#Weymouth_equation Weymouth equation] is an approximation used to calculate the flow in the pipe based on the pressures at either end. It is generally used for high-Reynolds-number flows where the Moody friction factor is merely a function of relative roughness.

The relation between pressures p_{m,n} at m,n and flow f_{mn} is given by:

f_{mn} = sgn(p_m,p_n) C_{mn} \sqrt{|p_m^2 - p_n^2|}

where sgn(p_m,p_n) =1 if p_m \geq p_n and sgn(p_m,p_n) = -1 if p_m < p_n.

= Publications on gas network modelling =

European Climate Foundation [https://europeanclimate.org/energy-union-choices-a-perspective-on-infrastructure-and-energy-security-in-the-transition/ Energy Union Choices: A Perspective on Infrastructure and Energy Security in the Transition], Report, 2016

Neumann, A., Rosellón, J. & Weigt, H. [http://link.springer.com/article/10.1007/s11067-014-9273-3 Removing Cross-Border Capacity Bottlenecks in the European Natural Gas Market—A Proposed Merchant-Regulatory Mechanism] Networks and Spatial Economics, March 2015, Volume 15, Issue 1, pp 149–181, [https://www.diw.de/documents/publikationen/73/diw_01.c.376700.de/dp1145.pdf DIW Working Paper]

Jessica Rövekamp [https://dokumente.ub.tu-clausthal.de/servlets/MCRFileNodeServlet/Document_derivate_00000154/Db112168.pdf Transportnetzberechnung zur Feststellung der Erdgasversorgungssicherheit in Deutschland unter regulatorischem Einfluss] - PhD Thesis, 2014, TU Clausthal - the references give a good literature overview

Jan Abrell, Hannes Weigt [https://wwz.unibas.ch/uploads/tx_x4epublication/Combined_dynamic_Abrell_Weigt_2014.05.pdf Investments in a Combined Energy Network Model: Substitution between Natural Gas and Electricity] WWZ Discussion Paper 2014/05

Jan Abrell, Clemens Gerbaulet, Franziska Holz, Casimir Lorenz and Hannes Weigt [http://www.diw.de/documents/publikationen/73/diw_01.c.425843.de/dp1317.pdf Combining Energy Networks The Impact of Europe's Natural Gas Network on Electricity Markets until 2050], 2013 DIW Working Paper

M. Geidl and G. Andersson [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.164.5417&rep=rep1&type=pdf Optimal Power Flow of Multiple Energy Carriers] IIEEE Transactions on Power Systems, 22(1), 2007

Michele Arnold, Goran Andersson [https://www.eeh.ee.ethz.ch/uploads/tx_ethpublications/Arnold_DecomposedElectricityandNaturalGasOPF.pdf Decomposed Electricity and Natural Gas Optimal Power]

Linearised Weymouth equations in:

Kjetil T. Midthun, Mette Bjørndal and Asgeir Tomasgard [http://www.jstor.org/stable/41323248 Modeling Optimal Economic Dispatch and System Effects in Natural Gas Networks], The Energy Journal, Vol. 30, No. 4 (2009), pp. 155-180

Further gas-electricity coupling in:

[http://iiesi.org/assets/pdfs/iiesi_102_mccalley1.pdf http://iiesi.org/assets/pdfs/iiesi_102_mccalley1.pdf]

[http://iiesi.org/assets/pdfs/101_mccalley_2.pdf http://iiesi.org/assets/pdfs/101_mccalley_2.pdf]