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| | {{Model | | {{Model |
| − | |Full_Model_Name=high spatial and temporal electricity system model | + | |Full_Model_Name=high spatial and temporal electricity system model |
| | |Acronym=highRES | | |Acronym=highRES |
| | |author_institution=UCL, UiO | | |author_institution=UCL, UiO |
| | |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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| − | Currently there is one version for Europe and one for GB. | + | Currently there is one version for Europe and one for GB. |
| | |open_source_licensed=Yes | | |open_source_licensed=Yes |
| | |license=MIT license (MIT) | | |license=MIT license (MIT) |
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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 |
| − | |sectors=Electricity, | + | |sectors=Electricity, |
| | |technologies=Renewables, Conventional Generation | | |technologies=Renewables, Conventional Generation |
| | |Demand sectors=Households, Industry, Transport, Commercial sector | | |Demand sectors=Households, Industry, Transport, Commercial sector |
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| | |Storage (Heat)=No | | |Storage (Heat)=No |
| | |decisions=dispatch, investment | | |decisions=dispatch, investment |
| | + | |georegions=EEA+Norway and UK |
| | + | |georesolution=Country level, 20 zones for GB |
| | |timeresolution=Hour | | |timeresolution=Hour |
| | |network_coverage=transmission, net transfer capacities | | |network_coverage=transmission, net transfer capacities |
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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 |
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)
