Building power grid resilience to extreme wildfire risks with distributed energy resources

Thesis

Climate change is a crucial issue for sustainable development in the 21st century. To mitigate and adapt to global warming, the Paris Agreement targets limiting global temperature rise to 2°C above pre-industrial levels. Since energy production is responsible for three-quarters of global carbon emissions, a sustainable energy transition is vital to achieving Net Zero and addressing climate change. Green electrification is central to this transition but also involves challenges, including the effects of extreme weather, ageing infrastructure, and the inherent intermittency of renewable generation on energy system optimisation. This DPhil study addresses these challenges by developing a resilient and sustainable power system model to withstand extreme weather risks, explicitly focusing on wildfires. The study is structured into four phases. Phase I developed a prototype Wildfire Energy Model (WEM) based on worst-case scenario simulations of the power grid in Victoria, Australia, during wildfire seasons. In Phase II, a Wildfire Resilient Load Forecasting Model (WRLFM) was constructed using deep learning techniques and multiple climate factors to predict energy consumption. Phase III extended the WEM to a dynamic time-series version, based on a modified IEEE 24-bus Reliability Test System, to generalise the model. In Phase IV, the time-series WEM was further developed using real-world data from Victoria to assess grid performance during the 2019-2020 wildfire season. Throughout the four phases, the study evaluates grid resilience from technical, economic, and environmental perspectives. The WRLFM was employed to account for system-wide uncertainties and calculate the probabilistic power reserve required during wildfire events in the generalised WEM. The results demonstrate that distributed energy sources are effective strategies for preventing blackouts and managing wildfire risks. This research proves the feasibility of building a resilient and sustainable grid that ensures safe operation, cost-efficiency, and decarbonisation in the face of extreme climate events.

Authors: Yang, W

• DOI: 10.5287/ora-vjmykpz4g
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English