Power System Resilience with Wildfires and Low Carbon Technologies

Donaldson, Daniel Lyle ORCID: 0000-0003-3419-3624 (2022). Power System Resilience with Wildfires and Low Carbon Technologies. University of Birmingham. Ph.D.

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Abstract

The world is becoming increasingly reliant on electricity as a result of decarbonisation efforts, necessitating an electric grid that is resilient to natural disasters. Wildfires can adversely impact the electric grid, requiring mitigation to limit disruption to customers. Evaluation of wildfire mitigation options in the planning horizon is necessary to provide sufficient time for implementation. The complex interaction between wildfires and low carbon technologies (LCTs) like electric vehicles (EV) and solar photovoltaic (PV) generation further complicates management of the grid during the operating horizon. As residents in the wildland-urban interface evacuate, EV charging introduces additional load volatility increasing the uncertainty. Smoke also limits solar radiation, reducing the available capacity of solar PV generation integrated power systems in affected areas. This thesis presents significant contributions to enhance wildfire resilience assessment in the planning horizon, integrating the effects of LCT adoption with geospatial visualisation to strengthen proactive mitigation efforts.

In order to identify robust mitigation plans, resilience metrics should be risk-informed, as expected value metrics are likely to under-estimate the risk of interruption during a period with extreme wildfires. This thesis primarily proposes an advanced framework to quantify wildfire resilience in the planning horizon. The uniqueness of the framework is the integration of satellite-derived empirical wildfire ignitions with grid topology to produce data for numerous synthetic wildfire seasons and presenting algorithms to quantify the risk over an entire year of events, rather than focusing on a single event. Leveraging the growth of solar PV generation and EVs in wildfire mitigation plans requires current knowledge of the location and anticipated performance of PV and EV installations. This thesis also provides an advanced agglomerative approach to robustly identify the location of solar prosumers, with net smart meter data. The approach employs piecewise-aggregate approximation to reduce the computational burden of the approach without compromising the accuracy. Wildfire smoke has far reaching effects, resulting in regional attenuation of PV production. This thesis further presents an innovative methodology to predict the derate to PV production to inform generation planning. The uniqueness of the methodology is the ability to use satellite-derived aerosol optical depth data to project the derate over a wide geographical region. Awareness of EV penetration level is important as loss of diversification in EV charging behaviour during a wildfire evacuation has the potential to increase the amount of power required from the grid. This problem is addressed in the thesis by presenting a novel algorithm that integrates behavioural factors and technical parameters of EVs to reflect the EV spatio-temporal charging demand throughout the evacuation process.

Geospatial visualisations resulting from the research findings provide practical and broad insight for power system wildfire resilience planning. The research findings presented in the thesis offer new tools to enhance wildfire resilience planning assessments in modern power systems.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):