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Type: Thesis
Title: When the Wind Blows: Vulnerability of Power Networks with High Renewable Penetration
Author: Willsmore, Fergus
Issue Date: 2020
School/Discipline: School of Mathematical Sciences
Abstract: Investigating the vulnerability of power networks gives us insight into the network elements that require reinforcement in order to maintain highly reliable power. The current state of climate has become of increasing concern, and has caused a rapid increase in renewable energy. Unlike conventional generation, renewable energy is highly dependent on the weather, potentially exposing network vulnerabilities to cascading failure and network congestion. A new model of Nesti et al. [38] investigates emergent cascades that arise from fluctuations in renewable energy. In particular, the authors use the theory of large deviations in order to rank the most-likely initial line failures. On the other hand, there are a number of studies that link frequent congestions to high wind penetration, and use generation re-dispatch in order to estimate wind curtailment. In this thesis, we first extend the initial emergent cascade model, by using the power spectrum to identify significant cycles in solar generation, and find that this decreases the probabilities of line failure. Then, we develop a new long-term congestion management model, which we use to investigate the impact of new wind farm connections on wind curtailment in the South Australian power network. We predict the power output of the new wind farms using a combination of linear regression, ARMA models and quantile regression. We find that the Mid-North has the largest amount of spare network capacity, and that transmission upgrades must coincide with the integration of new wind farms in the South East.
Advisor: Nguyen, Giang
Glonek, Garique
Vowles, David
Dissertation Note: Thesis (MPhil) -- University of Adelaide, School of Mathematical Sciences, 2020
Keywords: Revewable energy
complex networks
time series
regression analysis
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