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| | |authors=James Price, Marianne Zeyringer | | |authors=James Price, Marianne Zeyringer |
| | |website=https://github.com/highRES-model | | |website=https://github.com/highRES-model |
| − | |text_description=Welcome to the repository for the European version of the high temporal and spatial resolution electricity system model (highRES-Europe). The model is used to plan least-cost electricity systems for Europe and specifically designed to analyse the effects of high shares of variable renewables and explore integration/flexibility options. It does this by comparing and trading off potential options to integrate renewables into the system including the extension of the transmission grid, interconnection with other countries, building flexible generation (e.g. gas power stations), renewable curtailment and energy storage. | + | |text_description=The model is used to plan least-cost electricity systems for Europe and specifically designed to analyse the effects of high shares of variable renewables and explore integration/flexibility options. It does this by comparing and trading off potential options to integrate renewables into the system including the extension of the transmission grid, interconnection with other countries, building flexible generation (e.g. gas power stations), renewable curtailment and energy storage. |
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| | highRES is written in GAMS and its objective is to minimise power system investment and operational costs to meet hourly demand, subject to a number of system constraints. The transmission grid is represented using a linear transport model. To realistically model variable renewable supply, the model uses spatially and temporally-detailed renewable generation time series that are based on weather data. | | highRES is written in GAMS and its objective is to minimise power system investment and operational costs to meet hourly demand, subject to a number of system constraints. The transmission grid is represented using a linear transport model. To realistically model variable renewable supply, the model uses spatially and temporally-detailed renewable generation time series that are based on weather data. |
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| | |open_future=No | | |open_future=No |
| | |modelling_software=GAMS; CPLEX | | |modelling_software=GAMS; CPLEX |
| − | |processing_software=Phyton | + | |processing_software=Python |
| | |GUI=No | | |GUI=No |
| | |model_class=European electricity system model, GB electricity system model | | |model_class=European electricity system model, GB electricity system model |
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| | |math_modeltype=Optimization | | |math_modeltype=Optimization |
| | |math_objective=Minimization of total system costs | | |math_objective=Minimization of total system costs |
| − | |is_suited_for_many_scenarios=No | + | |is_suited_for_many_scenarios=Yes |
| | |montecarlo=No | | |montecarlo=No |
| | |computation_time_minutes=60 | | |computation_time_minutes=60 |
Latest revision as of 09:27, 11 February 2022
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high spatial and temporal electricity system model
by UCL, UiO
Authors:
James Price, Marianne Zeyringer
Contact:
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The model is used to plan least-cost electricity systems for Europe and specifically designed to analyse the effects of high shares of variable renewables and explore integration/flexibility options. It does this by comparing and trading off potential options to integrate renewables into the system including the extension of the transmission grid, interconnection with other countries, building flexible generation (e.g. gas power stations), renewable curtailment and energy storage.
highRES is written in GAMS and its objective is to minimise power system investment and operational costs to meet hourly demand, subject to a number of system constraints. The transmission grid is represented using a linear transport model. To realistically model variable renewable supply, the model uses spatially and temporally-detailed renewable generation time series that are based on weather data.
Currently there is one version for Europe and one for GB.
Based on GAMS; CPLEX. Using Python for data processing.
Website / Documentation
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 Open Source
MIT license (MIT)
 Not directly downloadable
Input data shipped
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| Model Scope |
Model type and solution approach |
| Model class
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European electricity system model, GB electricity system model
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| Sectors
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Electricity
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| Technologies
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Renewables, Conventional Generation
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| Decisions
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dispatch, investment
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| Regions
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EEA+Norway and UK
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| Geographic Resolution
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Country level, 20 zones for GB
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| Time resolution
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Hour
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| Network coverage
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transmission, net transfer capacities
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| Model type
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Optimization
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| Variables
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| Computation time
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60 minutes
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| Objective
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Minimization of total system costs
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| Uncertainty modeling
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| Suited for many scenarios / monte-carlo
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Yes
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References
Scientific references
Zeyringer, M., Price, J., Fais, B., Li, P.-H. & Sharp, E. Designing low-carbon power systems for Great Britain in 2050 that are robust to the spatiotemporal and inter-annual variability of weather. Nat. Energy 3, 395–403 (2018)
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