Dr D Brayshaw, Dr P Coker, Dr L Shaffrey
Applications accepted all year round
Self-Funded PhD Students Only
About the Project
Throughout the world, power systems are undergoing massive changes in response to the challenge of climate change. Renewable electricity (RE) sources – particularly those sensitive to weather, such as wind and solar PV – are playing an increasing role in many national power systems.
This growing dependence on weather-dependent RE generation fundamentally alters the way power systems operate. The traditional ‘model’, whereby the output from large power stations (e.g., coal, gas, nuclear) can be controlled to meet electricity demand, is being replaced by a situation in which neither demand nor supply can be fully controlled nor predicted. In Great Britain, an increasing reliance on wind power already means that difference between a windy and a calm winter has as much impact on the total generation required from traditional power stations as temperature [Bloomfield et al, ERL 2017], and low wind cold snaps (as opposed to simply cold snaps) have become a key stress point for supply security [Thornton et al, ERL 2017; Brayshaw et al, JRR 2012].
The ‘renewables integration’ challenge is faced by power systems across the world, raising an important question: how will climate variability and climate change affect the behaviour of power systems in the coming decades?
To understand the impact of climate on integrated power systems, one must first realise that the response of the power system to meteorological variability is very non-linear, with weather influencing the supply of and demand for power as well as the physical resilience of the grid infrastructure. Local meteorological properties at disparate locations can be closely interconnected, both in terms of physical climate (“teleconnection patterns” and other structures), but also because of transmission via the power grid. These complexities and connections produce new stress-points and opportunities for the power system as a whole – and these change as the power system evolves. Research at Reading has, for example, (1) developed new techniques to ‘optimise’ future RE deployments to reduce the day-to-day weather volatility of the European power grid [Santos-Alamillos et al, ERL in press], (2) highlighted the importance of NAO-negative winters as a key stress-point if Norwegian hydro-reserves are used to balance seasonal variability in wind power over the UK [Ely et al ERL 2013], and (3) demonstrated the need for multi-decadal climate data for robust power-system modelling [Bloomfield et al, ERL 2017].
This project will extend previous studies by using data from a new state-of-the-art, high-resolution, multi-model GCM inter-comparison project (PRIMAVERA, EU H2020) to systematically explore the impacts of climate variability and change on integrated power systems (initially focussing on Europe). Drawing on in-depth and process-based knowledge of the underlying atmospheric dynamics, the key goals will be to understand the physical meteorological processes causing extreme behaviour in the energy system, and to estimate the extent of these effects in economic and power-system terms (demand levels, prices, financial loss etc). Process-understanding of the coupling between power systems and weather/climate will be a focus.
TRAINING
The student will attend several MSc-level modules in Meteorology at the University of Reading in the first two terms. This globally recognized course provides a robust grounding in the fundamental atmospheric and climate processes. The student will also be encouraged to attend modules delivered in the School of Construction Management and Engineering from the MSc programme ‘Renewable Energy’ on a non-assessed basis.
The student will be encouraged to participate in relevant training workshops and events such as:
- UK Energy Research Centre summer schools
- ICEM education seminars (International Conference on Energy and Meteorology)
- OpenMod workshops (an international academic network promoting use of open source energy models)
- NCAS training courses (e.g., data analysis)
To read more about this project, please follow this link: http://www.met.reading.ac.uk/nercdtp/home/available/desc/entry2018/SC201819.pdf