English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The South Australia region of the Australian National Electricity Market(NEM) displays some of the highest levels of price volatility observed inmodern electricity markets. This paper outlines an approach to probabilisticforecasting under these extreme conditions, including spike filtration andseveral post-processing steps. We propose using quantile regression as anensemble tool for probabilistic forecasting, with our combined forecastsachieving superior results compared to all constituent models. Within ourensemble framework, we demonstrate that averaging models with varying traininglength periods leads to a more adaptive model and increased predictionaccuracy. The applicability of the final model is evaluated by comparing ourmedian forecasts with the point forecasts available from the Australian NEMoperator, with our model outperforming these NEM forecasts by a significantmargin.

A probabilistic forecast methodology for volatile electricity prices in the Australian National Electricity Market