PowerWeb Lecture: The impact of climate uncertainty on power system operations

08 juni 2022 16:15 t/m 17:15 - Locatie: Online | Zet in mijn agenda

By Dr. Hannah Bloomfield; University of Bristol

Hosted by the PowerWeb Institute
Date: Wednesday 8 June 2022
Moderator: Dr Francesco Lombardy

Click here to download the presentation
Click here to watch the recording

Power systems across the globe are rapidly decarbonising to meet carbon mitigation targets. This includes increasing the amount of installed renewable generation (from wind solar and hydropower) while electrifying the heat and transport sectors. In doing this the amount of meteorologically driven variability in power system operations has been increasing and is a key topic of research in the energy meteorological community.

In this talk Hannah will demonstrate examples from two recent publications how weather and climate variability can impact power system operations. The first compares the magnitude of climate uncertainty to uncertainty in demand modelling methodologies and plausible future heat pump installation scenarios. The second example examines the impacts of future climate change on power systems across Europe and demonstrates how the magnitude of weather and climate variability present is influenced by power system decarbonisation scenarios.

Hannah: "Throughout the talk open access weather and climate datasets for use in the energy sector will be referenced, and I am very happy to discuss the future usefulness and development of these."

Dr Hannah Bloomfield is a research scientist in climate risk analytics at the University of Bristol. She has spent the last eight years working at the University of Reading, studying the impacts of climate variability and climate change on national-level power systems. Hannah specialises in modelling UK and European electricity demand and renewable generation. She has also worked on developing these tools for Mexico, India and multiple regions of Africa. A key outcome of her work has been to improve the accessibility of large meteorological datasets to non-specialists.