highRES

The high spatial and temporal Resolution Electricity System model, highRES, is used to design cost-effective, flexible and weather resilient electricity systems for Great Britain and Europe. The model is specifically designed to analyse the effects of high shares of variable renewables and explore integration/flexibility options.

As the proportion of renewables in electricity generation increases, there will be increasing imbalances between electricity demand and supply. highRES is a high-resolution electricity system model that simultaneously considers infrastructure planning (investment) and operational (dispatch) decisions to identify the most cost-effective strategies to cope with growing shares of intermittent renewables. 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 unit and system constraints. It can model a variety of technical characteristics of thermal generators (e.g. ramping restrictions, minimum stable generation, startup costs, minimum up and down times) depending on the requirements of the research question, their CO2 emissions, and the technical characteristics of a variety of energy storage options. 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. For wind energy, hourly wind speed data from the ERA-5 climate reanalysis covering 1983-2017 is used, with a spatial resolution of 0.25 degrees x 0.25 degrees (~28 x 17 km). Hourly solar radiation data are taken from the Climate Monitoring Satellite Application Facility dataset SARAH2, again covering 1983-2017 at the same spatial resolution as the wind data.

Typically the model makes planning and dispatch decisions based on hourly time series for one snapshot year, however, this can be adapted as required by leveraging the flexibility of the input weather data (e.g. using 10 years of hourly data simultaneously to better capture the impact of inter-annual weather variability on system design).

The model complements the UK TIMES and European TIMES energy system models. The temporal resolution of these long term planning models is too low to fully capture the implications of high levels of renewables. highRES can be run iteratively with these models to identify more robust low-carbon electricity systems for the future.

Model summary

Documentation

Documentation will appear here when it is published.

Publications

Journal Papers

Moore, A., Price, J., & Zeyringer, M. (2018). The role of floating offshore wind in a renewable focused electricity system for Great Britain in 2050. Energy strategy reviews, 22, 270-278

Price, J., Zeyringer, M., Konadu, D., Mourão, Z. S., Moore, A., & Sharp, E. (2018). Low carbon electricity systems for Great Britain in 2050: An energy-land-water perspective. Applied energy, 228, 928-941

Zeyringer, M., Price, J., Fais, B., Li, P. H., & Sharp, E. (2018). Designing low-carbon power systems for Great Britain in 2050 that are robust to the spatiotemporal and inter-annual variability of weather. Nature Energy, 3(5), 395

Conference Papers

Zeyringer, M., Daly, H., et al. (2014). Spatially and Temporally Explicit Energy System Modelling to Support the Transition to a Low Carbon Energy Infrastructure - Case Study for Wind Energy in the UK. International Symposium for Next Generation Infrastructure Conference Proceedings (IIASA, Laxenburg, Austria).

Projects developing/using the model (include links)

The model development and application is supported by the wholeSEM project