Background and motivation
In order to reduce the impacts of climate change, the energy system needs to go through a process of deep decarbonisation. In the future, a coupling of the different energy sectors (electricity, heating and cooling, transport, industry, etc.) is expected, with electric power generation providing a higher share of the overall energy demand due to electrification. With electrification and an energy system almost entirely fuelled by renewable energy sources, the European target of CO2 reduction could be reached, mitigating the impacts of climate change. However, important sources of renewable energy, such as the wind and solar radiation, are dependent on weather variables, which means that they are strongly dependent of weather conditions and any spatial and temporal variation in them. It brings a challenge of ensuring that a power system based mainly on variable renewable energy (VRE) can provide the required adequacy, considering that consumption and demand need to be constantly balanced. The recent discussion in scientific literature on the feasibility of a VRE driven future highlights the importance of such analyses.
This PhD project is part of the larger project “Power system impacts of highly weather dependent future energy systems” (PSfuture). The project is motivated by the challenges in operating and planning power system due to growing installation of VRE sources. In addition to the adequacy issue, the challenges include knowing the spatial availability of VRE resources and their spatiotemporal dependencies to plan interconnection expansion and guarantee system balancing. The objective of PSfuture project is to model and quantify these challenges, providing scenarios towards 2050 of the entire Europe. The project aims to answer the following questions: 1) Considering the electrification and sector coupling and consequently the increase on electricity demand, “can VRE generation fulfil its potential to generate this vast amount of energy on the European scale while keeping costs low?”, and 2) Regarding adequacy and reserve requirements due to balancing, “is the highly weather dependent power system of the future reliable?”. The purpose of the PhD project is to provide scientific information to answer these questions.
Research objective and methodologies
The hypothesis of PSfuture is that VRE generation can feasibly produce most of the energy consumption in a future highly interconnected and sector coupled European power system. To ensure that, an understanding of the weather dependencies and its impacts on energy system is required. A power system analysis needs time series of meteorological variables, such as wind speed, solar radiation and temperature, which are further converted into electrical power variables. At this point, the works that analyse the future power systems are done taking into account only the technological aspects (e.g. development due cost reduction and VRE technology changes), and they use VRE data from historical period. On the other hand, studies that analyse impacts of climate changes on VRE are not extended to power system analysis. Thus, using climate modelling to produce data for scenario years towards 2050 allow the PSfuture to include also impacts of climate change in the power and energy system analyses.
The data needs to meet some requirements to enable the study, such as high spatial and temporal resolution. E.g. hourly 10 km x 10 km reanalysis data has been applied on system-level studies. Climate scenarios usually do not deliver this level of detail. Also, the model needs to be able to reproduce the weather patterns which drive the VRE generation and electric load, as well the natural variability in these patterns on different time scales. Multiple scenarios are required to expand the analysis regarding the different paths that climate change can take. Finally, it is necessary to quantify the uncertainties in the produced time series in order to estimate the level of uncertainty when planning the energy systems towards 2050. To attend that, the mesoscale model Weather Research and Forecast (WRF) will be used to create the time series of relevant meteorological quantities. In a first step, the model will be forced by reanalysis (data based in modelling and observation) in the historical period. Evaluation and possible calibration will be performed to ensure the model’s ability in reproducing historical weather patterns considering spatial distribution and spatiotemporal variability relevant for power system studies. In a second step, future climate scenarios will be produced forced by different representative concentration pathways (RCP). The innovative character of the PhD project is to develop an optimal way to provide time series relevant to power system analyses while considering climate change projections towards 2050, helping to go a step further towards decarbonisation.