Backbone - Revision history

Tomi J. Lindroos at 12:38, 15 November 2023

2023-11-15T12:38:11Z

Tomi J. Lindroos at 12:36, 15 November 2023

2023-11-15T12:36:11Z

Tomi J. Lindroos at 07:59, 15 November 2023

2023-11-15T07:59:29Z

Tomi J. Lindroos at 08:36, 14 November 2023

2023-11-14T08:36:25Z

Tomi J. Lindroos at 08:35, 14 November 2023

2023-11-14T08:35:06Z

Tomi J. Lindroos at 08:33, 14 November 2023

2023-11-14T08:33:48Z

Tomi J. Lindroos at 08:29, 14 November 2023

2023-11-14T08:29:17Z

Juha Kiviluoma at 11:19, 14 March 2022

2022-03-14T11:19:30Z

Juha Kiviluoma at 11:18, 14 March 2022

2022-03-14T11:18:56Z

Juha Kiviluoma at 11:14, 14 March 2022

2022-03-14T11:14:08Z

@@ Line 63: / Line 63: @@
 |citation_references=Helistö, N.; Kiviluoma, J.; Ikäheimo, J.; Rasku, T.; Rinne, E.; O’Dwyer, C.; Li, R.; Flynn, D. Backbone—An Adaptable Energy Systems Modelling Framework. Energies 2019, 12, 3388.
 |citation_doi=https://doi.org/10.3390/en12173388
-|report_references=Please see a longer list at:
+|report_references=Journal publications (updated 14.11.2023):
-https://gitlab.vtt.fi/backbone/backbone/-/wikis/More-information/List-of-publications
-−
 Journal publications (updated 14.11.2023):
-Model documentation (please cite this if looking for a generic Backbone reference)
+Model documentation. Please cite this if looking for a generic Backbone reference.
 Helistö, N., Kiviluoma, J., Ikäheimo, J., Rasku, T., Rinne, E., O’Dwyer, C., Li, R., & Flynn, D. (2019). Backbone - An adaptable energy systems modelling framework. Energies, 12(17), 3388. https://doi.org/10.3390/en12173388
@@ Line 102: / Line 99: @@
 Rasku, T., & Kiviluoma, J. (2019). A comparison of widespread flexible residential electric heating and energy efficiency in a future Nordic power system. Energies, 12(1), 5. https://doi.org/10.3390/en12010005
 Shared model data
 Ikäheimo, J., Purhonen, A., Lindroos, T.J., Rämä, M. and Harrison, E. Northern European Model. https://github.com/vttresearch/north_european_model
 Lindroos, T.J., and Pursiheimo, E. Helsinki Region DHC model. https://gitlab.vtt.fi/backbone/models/helsinki-dhc-model
 |example_research_questions=Cost efficient future energy systems with high shares of variable power generation. Exploring the impact of operational details on energy system planning. Optimizing the use of storages and energy intensive processes that have days-long time delays (model temporal structure can change during the horizon).
 |Model validation=Comparison against two other models: https://doi.org/10.3390/en12173388

@@ Line 102: / Line 102: @@
 Rasku, T., & Kiviluoma, J. (2019). A comparison of widespread flexible residential electric heating and energy efficiency in a future Nordic power system. Energies, 12(1), 5. https://doi.org/10.3390/en12010005
 |example_research_questions=Cost efficient future energy systems with high shares of variable power generation. Exploring the impact of operational details on energy system planning. Optimizing the use of storages and energy intensive processes that have days-long time delays (model temporal structure can change during the horizon).
 |Model validation=Comparison against two other models: https://doi.org/10.3390/en12173388

@@ Line 2: / Line 2: @@
 |Full_Model_Name=Backbone - energy systems model
 |Acronym=Backbone
-|author_institution=VTT Technical Research Centre of Finland; University College Dublin
+|author_institution=VTT Technical Research Centre of Finland
 |authors=Juha Kiviluoma, Erkka Rinne, Topi Rasku, Niina Helistö, Jussi Ikäheimo, Dana Kirchem, Ran Li, Ciara O'Dwyer, Jussi Ikäheimo, Tomi J. Lindroos, Eric Harrison
 |contact_persons=Tomi J. Lindroos
@@ Line 44: / Line 44: @@
 |georegions=Depends on user
 |georesolution=Depends on user
-|timeresolution=Hour
+|timeresolution=15 Minute
 |network_coverage=transmission, DC load flow, net transfer capacities
 |Observation period=More than one year

@@ Line 60: / Line 60: @@
 |computation_time_minutes=10
 |computation_time_hardware=Normal laptop
-|computation_time_comments=Simple models can solve in seconds, complicated Europe-level models typically solve full year in ~hour
+|computation_time_comments=Simple models can solve full year in seconds, complicated European models with 20+ regions and many sectors typically solve full year in ~hour
 |citation_references=Helistö, N.; Kiviluoma, J.; Ikäheimo, J.; Rasku, T.; Rinne, E.; O’Dwyer, C.; Li, R.; Flynn, D. Backbone—An Adaptable Energy Systems Modelling Framework. Energies 2019, 12, 3388.
 |citation_doi=https://doi.org/10.3390/en12173388

@@ Line 6: / Line 6: @@
 |contact_persons=Tomi J. Lindroos
 |contact_email=Tomi.J.Lindroos@vtt.fi
-|source_download=https://gitlab.vtt.fi/backbone/backbone
+|source_download=https://gitlab.vtt.fi/backbone/backbone/-/tree/release-3.x
 |text_description=Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS).
 |Primary outputs=Costs, emissions, generation, consumption, transfers
@@ Line 18: / Line 18: @@
 |license=GNU Library or "Lesser" General Public License version 3.0 (LGPL-3.0)
 |model_source_public=Yes
-|Link to source=https://gitlab.vtt.fi/backbone/backbone
+|Link to source=https://gitlab.vtt.fi/backbone/backbone/-/tree/release-3.x
 |data_availability=some
 |open_future=No

@@ Line 53: / Line 53: @@
 |math_modeltype=Optimization
 |math_modeltype_shortdesc=The model minimizes the objective function and includes constraints related to energy balance, emissions, unit operation, transfers, system operation, portfolio design, etc.
 |math_objective=Cost minimization; emission minimization;
 |deterministic=Short-term and long-term stochastics are available
 |is_suited_for_many_scenarios=Yes
@@ Line 66: / Line 66: @@
 https://gitlab.vtt.fi/backbone/backbone/-/wikis/More-information/List-of-publications
-Journal publications (updated 14.3.2022):
+Journal publications (updated 14.11.2023):
 Helistö, N., Kiviluoma, J., Morales-España, G. & O’Dwyer, C. (2021). Impact of operational details and temporal representations on investment planning in energy systems dominated by wind and solar. Applied Energy, 290, 116712. https://doi.org/10.1016/j.apenergy.2021.116712
@@ Line 72: / Line 85: @@
 Helistö, N., Kiviluoma, J., & Reittu, H. (2020). Selection of representative slices for generation expansion planning using regular decomposition. Energy, 211, 118585. https://doi.org/10.1016/j.energy.2020.118585
-Rasku et al. Impact of 15-day energy forecasts on the hydro-thermal scheduling of a future Nordic power system. Energy
+Rasku, T., Miettinen, J., Rinne, E., & Kiviluoma, J. (2020). Impact of 15-day energy forecasts on the hydro-thermal scheduling of a future Nordic power system. Energy, 192, 116668. https://doi.org/10.1016/j.energy.2019.116668
-Volume 192, 1 February 2020, 116668. https://doi.org/10.1016/j.energy.2019.116668
 Kiviluoma, J., O'Dwyer, C., Ikäheimo, J., Lahon, R., Li, Ran, Kirchem D., Helistö, N., Rinne, E., Flynn, D. (2022) Multi-sectoral flexibility measures to facilitate wind and solar power integration. IET Renew. Power Gener.,  https://doi.org/10.1049/rpg2.12399
@@ Line 81: / Line 101: @@
 Lindroos, T. J., Mäki, E., Koponen, K., Hannula, I., Kiviluoma, J., & Raitila, J. (2021). Replacing fossil fuels with bioenergy in district heating – Comparison of technology options. Energy, 231, [120799]. https://doi.org/10.1016/j.energy.2021.120799
-Rasku, T. & Kiviluoma, J. A Comparison of Widespread Flexible Residential Electric Heating and Energy Efficiency in a Future Nordic Power System.  Energies 2019, 12(1), 5; https://doi.org/10.3390/en12010005
+Rasku, T., & Kiviluoma, J. (2019). A comparison of widespread flexible residential electric heating and energy efficiency in a future Nordic power system. Energies, 12(1), 5. https://doi.org/10.3390/en12010005
-−
-Pursiheimo, E., & Kiviluoma, J. (2021). Analyzing electrification scenarios for the northern European energy system. In Electrification (pp. 271-288). Academic Press.
 |example_research_questions=Cost efficient future energy systems with high shares of variable power generation. Exploring the impact of operational details on energy system planning. Optimizing the use of storages and energy intensive processes that have days-long time delays (model temporal structure can change during the horizon).
 |Model validation=Comparison against two other models: https://doi.org/10.3390/en12173388

@@ Line 3: / Line 3: @@
 |Acronym=Backbone
 |author_institution=VTT Technical Research Centre of Finland; University College Dublin
-|authors=Juha Kiviluoma, Erkka Rinne, Topi Rasku, Niina Helistö, Jussi Ikäheimo, Dana Kirchem, Ran Li, Ciara O'Dwyer
+|authors=Juha Kiviluoma, Erkka Rinne, Topi Rasku, Niina Helistö, Jussi Ikäheimo, Dana Kirchem, Ran Li, Ciara O'Dwyer, Jussi Ikäheimo, Tomi J. Lindroos, Eric Harrison
-|contact_persons=Juha Kiviluoma, Erkka Rinne
+|contact_persons=Tomi J. Lindroos
-|contact_email=juha.kiviluoma@vtt.fi, erkka.rinne@vtt.fi
+|contact_email=Tomi.J.Lindroos@vtt.fi
 |source_download=https://gitlab.vtt.fi/backbone/backbone
 |text_description=Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS).
@@ Line 14: / Line 14: @@
 |Code documentation=Formulas: https://doi.org/10.3390/en12173388; Code documentation: within code
 |Source of funding=Academy of Finland; ESIPP project (Ireland)
-|Number of developers=8
+|Number of developers=11
 |open_source_licensed=Yes
 |license=GNU Library or "Lesser" General Public License version 3.0 (LGPL-3.0)
 |model_source_public=Yes
 |Link to source=https://gitlab.vtt.fi/backbone/backbone
 |open_future=No
 |modelling_software=GAMS
-|processing_software=Spine Toolbox forthcoming. Currently Excel / SQL.
+|processing_software=Spine Toolbox or Excel
 |GUI=No
 |model_class=Framework
@@ Line 47: / Line 48: @@
 |Observation period=More than one year
 |Additional dimensions (Ecological)=Depends on data
-|Additional dimensions (Economical)=-
+|Additional dimensions (Economical)=Depends on data
 |Additional dimensions (Social)=-
 |Additional dimensions (Other)=-
 |math_modeltype=Optimization
-|math_modeltype_shortdesc=The model minimizes the objective function and includes constraints related to energy balance, unit operation, transfers, system operation, portfolio design, etc.
+|math_modeltype_shortdesc=The model minimizes the objective function and includes constraints related to energy balance, emissions, unit operation, transfers, system operation, portfolio design, etc.
-|math_objective=Cost minimization
+|math_objective=Cost minimization; emission minimization;
 |deterministic=Short-term and long-term stochastics are available
 |is_suited_for_many_scenarios=Yes
 |number_of_variables=1000000
 |montecarlo=No
-|computation_time_minutes=1000
+|computation_time_minutes=10
-|computation_time_comments=The implementation leads to reasonable computation time, but we plan to improve calculation time in future.
+|computation_time_hardware=Normal laptop
 |citation_references=Helistö, N.; Kiviluoma, J.; Ikäheimo, J.; Rasku, T.; Rinne, E.; O’Dwyer, C.; Li, R.; Flynn, D. Backbone—An Adaptable Energy Systems Modelling Framework. Energies 2019, 12, 3388.
 |citation_doi=https://doi.org/10.3390/en12173388
-|report_references= Please see a longer list at:
+|report_references=Please see a longer list at:
 https://gitlab.vtt.fi/backbone/backbone/-/wikis/More-information/List-of-publications
@@ Line 86: / Line 88: @@
 |Comment on model validation=Produces similar unit commitment results as a commercial tool in wide-spread use.
 |Specific properties=Flexible temporal and technological detail. An energy systems model with capability for detailed unit commitment of the power system. Can include operational detail in generation/transmission planning.
-|Interfaces=Spine Toolbox forthcoming.
+|Interfaces=Excel or Spine Toolbox
 |Model input file format=No
 |Model file format=No
 |Model output file format=No
 }}