Abstract
This study applies dynamic network analysis to the power sector, examining the relationship between regional spot electricity prices in the Australian National Electricity Market (NEM). In particular, we employ principal component analysis and generate Granger causality networks to examine the degree of interconnectedness of the NEM in a time-varying setting. We find that the derived measures of interdependence can be related to actual market events such as price spikes, unexpected high demand for electricity, sudden increases in price volatility, rebidding of dominant generators, the temporary or permanent outage of major power stations, and upgrades and limitations in transmission capacity. In the analysed network, we find that stronger dependence is exhibited by regional markets that are linked through interconnectors, while the direction of Granger causality can be related to interregional trade. We further examine the usefulness of the derived measures for forecasting distributional characteristics of spot prices such as the maximum price, volatility, price spreads, or upcoming periods of price spikes. Our results suggest that the derived network measures have predictive power, albeit limited, for the behaviour of spot electricity prices in the NEM.
Original language | English |
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Article number | 104972 |
Pages (from-to) | 1-20 |
Number of pages | 20 |
Journal | Energy Economics |
Volume | 92 |
DOIs | |
Publication status | Published - 1 Oct 2020 |
Keywords
- Dependence and interconnectedness
- Dynamic networks
- Electricity markets
- Multivariate analysis
- Risk management
- Spot prices