Introducing climate variability in energy systems modelling. (1st September 2020)

• Record Type: Journal Article
• Authors: Amorim, Filipa; Simoes, Sofia G.; Siggini, Gildas; Assoumou, Edi
• Is Part Of: Energy. Volume 206(2020)
• Publication Date: 2020-09-01
• Subjects: Climate/energy modeling -- Climate variability -- Spatial and temporal disaggregation -- Climate change and adaptation -- Renewable power; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118089
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper presents the ongoing research within Clim2Power project Portuguese case study. Its main goal (as a first step) is to show the relevance of using a highly detailed spatial and temporal modeling tool of the Portuguese electricity system in order to be able to adequately capture climate variability in the planning of the system up to 2050. To do so, we consider seasonal and intraday hydro, wind and solar resources variability in a large TIMES energy system model, in the eTIMES_PT model. Existing hydro, wind and thermal powerplants are modelled individually, whereas new plants are modelled at municipality level. The importance of introducing climate variability is assessed by modeling six scenarios: a reference case and both "humid" and "dry" hydropower scenarios. Each of these is also modelled with CO2 emissions cap by 2050. Results show that hydropower electricity generation variations are within range of those referred in literature by other authors. However, in this work, we are able to capture higher variations within seasons and time of day. Also, the analysis enables to account for the combined variability of hydro, PV and wind resources. This variability will subsequently consider data from seasonal forecasts and climate projections. Highlights: Clim2Power project Portuguese case study research is presented. Developed a very detailed modeling tool for the Portuguese power system. Consider 64 annual time-slices, seasonal/intraday hydro, wind and solar variability. Existing plants modelled individually and new plants at municipality level. Found that future hydropower variations slightly higher than those in literature.